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Autobooks

We're Just Riding the Ups and Downs of Investing in Bitcoin

HackerNoon Reporter: Please tell us briefly about your  background. I am a ‘late start’ female founder from Ghana after a 25+ years successful career in IT for Development, Service Delivery and Content Creation. I am fuelled by a passion for books & the immense potential of the internet and mobile phones for spreading African knowledge. What's your startup called? And in a sentence or two, what does it do? AkooBooks Audio is a platform and experience provider focused on transforming Black/African books into engaging audiobooks that reach new audiences on mobile phones. Our library of African audio is available anytime, accessible anywhere on a wide variety of mobile devices at flexible subscription plans and low retail cost in various Ghanaian and African languages and not only in English. What is the origin story? The seeds for my business were first inspired by my mother, Nana Dadson, a children's book author and avid reader. My mother lost her vision over a decade ago and unfortunately with that her ability to read African literature independently, as only a fraction is available in digital form. Soon, AkooBooks Audio was born. Akoobooks Audio What do you love about your team, and why are you the ones to solve this problem? We are creating a literate social environment that goes beyond equipping schools with textbooks and libraries and enabling  learners to use their knowledge appropriately and meaningfully in everyday life. Shortage of reading material for effective literacy, limited know-how and slow adoption of digital book distribution prevent efficient and effective African knowledge transfer and stunt our growth in the digital economy. With Africa recording the highest penetration of the use of mobile phones, the potential of audiobooks  and digital reading comes in. Our team has over 30 years combined experience in technology, publishing, entertainment and media. If you weren’t building your startup, what would you be doing? Mothering my teenager and planning how to open up a restaurant/cafe. At the moment, how do you measure success? What are your core metrics? We look at the number of titles in our catalogue and  currently run a retail per streaming download model. As a digital publishing company, subscriptions are fast becoming a a way of competing with other online entertainment models that are free. We want to move to an all you can eat streaming model. Mobile platform offers new sources to inform decision making, we share  data with publishers to help them make the right production choices for future catalogues. Our key performance indicators (KPIs) for our audiobooks include: a) Relevance- how many users start listening to an audiobook; b)Drop off rate- how many users stop listening to an audiobook c) Finish rate-how many users finish the book to the end. Also, data on preferences, Narrators, Genres and Barriers. What’s most exciting about your traction to date? We’ve won 3 business awards that  have enabled us to roll out our web based African audiobook platform which is  also available on the Google and Apple playstores. We have licensed over 300 African titles from African publishers all over the African continent. We hope to partner the Ministry of Education to bring digital books into Ghanaian classrooms. What technologies are you currently most excited about, and most worried about? And why? Audio and AI/machine technology. Our programme promotes audio literacy and pilots it in local languages, bringing a wealth of ideas and experiences to people who are illiterate in English. We see the opportunity to skip the translation phase of books and go directly from English audio into producing ‘straight into audio’ local language versions. The new interpreted local language adaptations can then be transcribed in local languages and form the basis for new local language literature for young people. With our audio data, Akoobooks Audio is at the forefront of utilizing African voice interaction and ML technology to connect African books and authors to new readers worldwide. What drew you to get published on HackerNoon? What do you like most about our platform? I have only been following the platform for a few months and pleasantly surprised to find a good coverage of African tech content that is engaging and insightful. What advice would you give to the 21-year-old version of yourself? To be positive and believe in myself. When I encounter failure, take a step back and realize that failure is part of life and to ask myself if there are any lessons to be learned or if there are other ways around it. Being a woman in a male dominated career space like tech or publishing can be challenging, but our femininity is our greatest strength. What is something surprising you've learned this year that your contemporaries would benefit from knowing? Overseas capital is flooding the African fintech and African digital streaming subscription services market for entertainment (movies -Netflix and music -Spotify). I look forward to seeing similar developments in the online reading space! Vote for Accra Startups of the Year!

My Mother Lost Her Vision, So I Made African Books into Engaging Audiobooks

Isn’t it interesting? So basically after reading this article you don’t need to read long PDFs which contains more than 10 pages and only with help of 12 lines Python code. I’ll explain every line of code so even who doesn’t have knowledge of Python, can understand the code. So let’s start!! Here’re the steps to follow for making an AudioBook: First of all you must have Python and it’s IDE installed on your PC If you don’t have these installed you can do it just by clicking on and . There are many IDEs but I’m giving you link of PyCharm because it is easy to use and open-source. If you don’t know IDE than no worry about it’s just a code editor for Python. Python IDE After downloading both Python and PyCharm you have to set it’s environment and for that there are many videos on YouTube so take help from them. Let’s open IDE and create a new file and give it a name whatever you want. Click on Terminal option then just installed Python text to speech library just like this : (pyttsx3) pip install pyttsx3 #make sure you are connected with Internet Also install PyPDF2 library in same way: pip install PyPDF2 : Here is the full code pyttsx3 PyPDF2
pdf_book = ( , )
pdf_book_reader = PyPDF2.PdfFileReader(pdf_book)
pages_no = pdf_book_reader.numPages
print(pages_no)
speaker = pyttsx3.init() number range( ,pages_no):
  page_start = 
  pdf_book_reader.getPage( ) = page_start.extractText()
  speaker.say( )
  speaker.runAndWait() import import open 'book.pdf' 'rb' for in 8 8 text text Explanation of code: In line 1 & 2 import required libraries. In line 3 , create a variable called which is used to open the pdf file which we want to make speak and ‘rb’ is to read in binary. pdf_book In line 4, read the file which we want to make speak using function of library. pdf_book_reader = PyPDF2.PdfFileReader(pdf_book) PdfFileReader PyPDF2 In line 5, counting total number of pages in the file using numPages function. pages_no = pdf_book_reader.numPages In line 6, displays total number of pages in the file. print(pages_no) In line 7, initiate the pyttsx3 library to speak the file. speaker = pyttsx3.init() In line 8, a for loop is initiated to iterate through whole pdf file from starting page to ending page using range function. for number in range(8,pages_no): In line 9, starting page from where we want to make Python to read. page_start = pdf_book_reader.getPage(8) In line 10, text = extracting the text from starting page using function. page_start.extractText() extractText() In line 11, speaking the text from PDF file pages using say function. speaker.say(text) In line 12, making sure that it speaks all pages for PDF file speaker.runAndWait() So now you can lay on your bed and just listen whatever PDF you want to speak anytime, anywhere from Python just by running this program. Note: I’ll suggest you to put the PDF file in the same folder where you are writing code and it’ll reduce your trouble. Thank you so much for reading! follow the writer of the article for more stuff on Python and Data Science.

How To Convert PDFs Into AudioBooks

Young children are always told to read more books to increase their performance at school, as well as help with their cognitive development. Reading books is a hobby that inculcates creativity, vocabulary, patience and concentration, however, in today’s fast-paced world, it might be a little hard to completely devote some time of the day simply to reading. Therefore, today, it has become almost a novelty to own a large collection of books and more importantly, to have the kind of time to actually read them all. This is understandable, of course, because reading is an intensive exercise that requires undivided attention from our minds and at the same time, needs our eyes and ears to be focused on that one aspect only. It is only natural that most people today may not find that kind of time and space in their everyday lives. If find yourself looking for a break from reality from time-to-time to drown in a story, audiobooks may just be what you are looking for. What are audiobooks? In very simple terms, audiobooks are simply voice recordings of stories from physically written books. These are available on numerous apps and websites and can be heard from any digital device like a laptop, smartphone, tablet or iPod. The debate surrounding the nature of audiobooks vs physical books focuses on whether this new innovation aims to take away from the habit of reading. A lot of people who love to read consider audiobooks as a “cheat” escape, meaning that these are not nearly as good as actual books but can perform the same functions. In light of this, it is important to point out some very important ways audiobooks have been more accommodating when it comes to our busy lives. How have audiobooks improved into our lives? have become very popular because they sync so perfectly with our busy lives. However, other than the obvious argument about how convenient it is for people to actually integrate it, there are many other benefits for relying on these, even for young kids. Some of these include: Audiobooks They don't deteriorate your vision One of the main problems with reading from books and tablets is that it gives a lot of respite to the eyes. For a lot of people with vision problems, reading can be very stressful to their eyes, despite reading from devices that do not give out any glare. Audiobooks do not require any visual reading and therefore, they are an ideal choice for people who especially suffer from vision problems. They don't take away from sleeping hours Glare from tablets and other devices can not only affect the eyes but also affect the circadian rhythm, which in turn affects sleep patterns. Therefore, audiobooks will also help you get a restful night of sleep. A lot of people use audiobooks as ASMR as well, since this can lull them into sleeping more easily. Audiobooks can help with time management Since audiobooks are designed to gel perfectly with our daily lives, they do not require people to devote time separately to simply listening to them. These can be listened to at any point of time, while driving, or having a bit of a break at the office, in between classes, while taking a walk or just while lazing around. This helps people who have very little time at hand and therefore cannot indulge in reading because they feel they will squander away whatever little free time they have. Moreover, if audiobooks are enjoyed while doing mundane everyday jobs, the experience can become more enjoyable. For example, you may dislike doing the dishes, but if you make it a point to listen to an audiobook while you do your dishes, you will find that you no longer feel like the task is a compulsion, and you will get it accomplished much faster. Audiobooks can help with pronunciation One of the prime requirements for being an audiobook narrator is having a soothing voice with flawless pronunciation. While this is a relatively less-explored advantage of listening to audiobooks, one has to agree that they help in pronunciation and developing a better vocabulary. This is very useful for young children, who can learn new words and correct pronunciations by listening to audiobooks. Migrants and people learning a second or a third language will also reap the benefits from this since continuously listening to audiobooks will directly help them with learning the language better. Audiobooks are just as helpful as reading physical books Numerous researchers say that the same parts of the brain are stimulated while reading a book or listening to an audiobook. The same cognitive and emotional responses have been noticed irrespective of the kind of medium they are read/listened to. This means recollection of information is the same regardless of the medium. It can be more emotionally intimate A lot of us like it when someone narrates a story to us. In this case, we can be the third person who witnesses the interaction between all the characters. This is why a lot of people connect better to audiobooks than they do with reading. It is a more affordable solution One of the reasons a lot of people steer away from reading is because books are not necessarily cheap, and they also require a lot of space and maintenance. For example, for those who have a hobby of reading, you may invest in a glare-free device or in lots of books, which is not always the most affordable solution. Therefore, audiobooks are an affordable alternative, where you can simply use the device you are already on, without having to buy more books and keep looking for space to store them. Other than these, a lot of people have affirmed that listening to audiobooks has been very helpful for them in dealing with mental health issues like anxiety. Reading a book might feel like a huge task that takes up time, but when it comes to listening to an audiobook, a person can feel that they are multitasking, as they are not necessarily squandering away their time and also engaging in a hobby simultaneously. Therefore, one can see that audiobooks suit our busy lifestyles so that we can enjoy a few minutes of quiet retreat without necessarily feeling unproductive. This in no way implies that reading books should no longer be followed, of course. However, for people who might feel like they are getting distanced from their hobbies, audiobooks can be a great way to rekindle that relationship they once had with stories. About The Author While a lot of websites offer audiobooks in different languages, at , we specifically focus on bringing back the lost taste of Indian classics from the likes of Premchand, Amrita Pritam and so on. We aim to bring Indian literature to all sections of society and our audiobooks range from stories, poems and motivational speeches. Gaatha Also published at https://gaatha850.medium.com/audiobooks-how-have-helped-our-busy-lives-by-gaatha-9aa3de919e2a

Audiobooks Provide The Same Cognitive Recollection as Physical Books Do 

Inspired by the , I’ve decided to share a collection of my favorite audiobooks and podcasts that I think HN readers will love. This is the best stuff I have discovered over the past 3–4 years, and I’m sure you guys will enjoy each of these books, so if you haven’t read some of them yet — I highly recommend you to check them out. recent HN thread Excellent audiobooks _From the founders of the trailblazing software company 37signals, here is a…_www.audible.com Rework _From Ed Catmull, co-founder (with Steve Jobs and John Lasseter) of Pixar…_www.audible.com Creativity, Inc. _Check out this great listen on Audible.com. 2015 Audie Award WINNER, Science Fiction 2015 Audie Award Finalist, Solo…_www.audible.com The Martian _Check out this great listen on Audible.com. Ben Horowitz, cofounder of Andreessen Horowitz and one of Silicon Valley…_www.audible.com The Hard Thing About Hard Things _Check out this great listen on Audible.com. Every moment in business happens only once. The next Bill Gates will not…_www.audible.com Zero to One _Check out this great listen on Audible.com. Jeff Hawkins, the man who created the PalmPilot, Treo smart phone, and…_www.audible.com On Intelligence _Check out this great listen on Audible.com. First, businesses discovered quality as a key competitive edge; next came…_www.audible.com The Design of Everyday Things _Check out this great listen on Audible.com. With his characteristic eyebrow-raising behavior, Richard P. Feynman once…_www.audible.com Surely You're Joking, Mr. Feynman! _Check out this great listen on Audible.com. Yuval Noah Harari, author of the critically acclaimed New York Times best…_www.audible.com Homo Deus _Check out this great listen on Audible.com. Atlas Shrugged is the "second most influential book for Americans today…_www.audible.com Atlas Shrugged _Check out this great listen on Audible.com. Map the innovation space - and blaze a path to profits and growth…_www.audible.com Mapping Innovation _Check out this great listen on Audible.com. Kevin Mitnick, the world's most famous hacker, teaches you easy cloaking…_www.audible.com The Art of Invisibility _Check out this great listen on Audible.com. The new era of gamification and human-focused design optimizes for…_www.audible.com Actionable Gamification _Check out this great listen on Audible.com. A fascinating exploration of how computer algorithms can be applied to our…_www.audible.com Algorithms to Live By _Check out this great listen on Audible.com. One of Silicon Valley's most successful angel investors shares his rules…_www.audible.com Angel _Check out this great listen on Audible.com. The mastermind behind Apple Computer sheds his low profile and steps…_www.audible.com iWoz _Check out this great listen on Audible.com. Most startups don't fail because they can't build a product. Most startups…_www.audible.com Traction Excellent podcasts YCombinator https://soundcloud.com/akharris Indie Hackers https://www.indiehackers.com/podcast Syntax (React and WebDev) https://syntax.fm/ Rationally Writing http://alexanderwales.com/rationally-writing/ Audio version of Harry Potter and the Methods of Rationality http://www.hpmorpodcast.com/ Audio version of Rationality: From AI to Zombies https://from-ai-to-zombies.eu/

Top audiobooks for Startup Founders

Table of Contents A Deep Dive into Voice Cloning with SoftVC VITS and Bert-VITS2 Prepare Dataset Extract from a Song UVR Workflows Preparation for vocal recording Cheapskate’s Audio Equipment Audacity workflows audio-slicer Cleaning dataset Match loudness so-vits-svc Set up environment Initialization Download pre-trained models Dataset Preparation Edit Configs Training Inference Audio Editing so-vits-svc-fork Installation Preparation Training Inference DDSP-SVC Preparation Training Inference Bert-vits2-V2.3 Initialization Preparation Transcription Training and Inference vits-simple-api Tweaks Share models In the , I tried a little bit of and found it interesting. So, I decided to train a usable model with my own voice. previous post TTS Generation WebUI This voice cloning project explores both SVC for Voice Changing and for Text-to-Speech. There is no one tool that does all jobs. VITS I have tested several tools for this project. Many of the good guides, like , , and , are in Chinese. So, I thought it would be useful to post my notes in English. this this this Although has been archived for a few months, probably due to oppression, it is still the tool for the best result. so-vits-svc Other related tools such as , , , and provide either faster/liter optimization, more features, or better interfaces. so-vits-svc-fork so-vits-svc-5.0 DDSP-SVC RVC But with enough time and resources, none of these alternatives can compete with the superior result generated by the original so-vits-svc. For TTS, a new tool called works fantastically and has already matured with its final release last month. It has some very different use cases, for example, audio content creation. Bert-VITS2 Prepare Dataset The audio files of the dataset should be in WAV format, 44100 Hz, 16bit, mono, 1-2 hours ideally. Extract From a Song is the easiest tool for this job. There is a that explains everything in detail. Ultimate Vocal Remover thread UVR Workflows Remove and extract Instrumental Model: VR - UVR(4_HP-Vocal-UVR) Settings: 512 - 10 - GPU Output and unclean vocal Instrumental Remove and extract background vocals. Model: VR - UVR(5_HP-Karaoke-UVR) Settings: 512 - 10 - GPU Output and unclean main vocal background vocal Remove reverb and noise. Model: VR - UVR-DeEcho-DeReverb & UVR-DeNoise Settings: 512 - 10 - GPU - No Other Only Output clean main vocal (Optional) Using RipX (non-free) to perform a manual fine-cleaning. Preparation for Vocal Recording It’s better to record in a treated room with a condenser microphone, otherwise, use a directional or dynamic microphone to reduce noise. Cheapskate’s Audio Equipment The very first time I got into music was during high school, with the blue Sennheiser MX500 and Koss Porta Pro. I still remember the first time I was recording a song that was on a Sony VAIO with Cool Edit Pro. Nowadays, I still resist spending a lot of money on audio hardware as an amateur because it is literally a money-sucking black hole. Nonetheless, I really appreciate the reliability of those cheap production equipment. The core part of my setup is a Behringer UCA202, and it’s perfect for my use cases. I bought it for $10 during a price drop. It is a so-called “Audio Interface” but basically just a sound card with multiple ports. I used RCA to 3.5mm TRS cables for my headphones, a semi-open K240s for regular output, and a closed-back HD669/MDR7506 for monitor output. All three mentioned headphones are under $100 for the normal price. And there are clones from Samson, Tascam, Knox Gear, and more out there for less than $50. For the input device, I’m using a dynamic microphone for the sake of my environmental noises. It is an SM58 copy (Pyle) + a Tascam DR-05 recorder (as an amplifier). Other clones such as SL84c or wm58 would do it too. I use an XLR to 3.5mm TRS cable to connect the microphone to the MIC/External-input of the recorder, and then use an AUX cable to connect between the line-out of the recorder and the input of the UCA202. It’s not recommended to buy an “audio interface” and a dedicated amplifier to replicate my setup. A $10 c-media USB sound card should be good enough. The Syba model that I owned is capable of “pre-amping” dynamic microphones directly and even some lower-end phantom-powered microphones. The setup can go extremely cheap ($40~60), but with UCA202 and DR-05, the sound is much cleaner. And I really like the physical controls, versatility, and portability of my old good digital recorder. Audacity Workflows Although when I was getting paid as a designer, I was pretty happy with Audition. But for personal use on a fun project, Audacity is the way to avoid the chaotic evil of Adobe. Noise Reduction Dereverb Truncate Silence Normalize audio-slicer Use or to slice the audio file into small pieces for later use. audio-slicer audio-slicer (gui) The default setting works great. Cleaning Dataset Remove those very short ones and re-slice those that are still over 10 seconds. In case of a large dataset, remove all that are less than 4 sec. In the case of a small dataset, remove those only under 2 sec. If necessary, perform a manual inspection for every single file. Match Loudness Use Audacity again with ; 0db should do it. Loudness Normalization so-vits-svc Set Up the Environment Virtual environment is essential to run multiple Python tools inside one system. I used to use VMs and Docker, but now, I found that is way quicker and handier than the others. anaconda Create a new environment for so-vits-svc, and activate it. conda create -n so-vits-svc python=3.8
conda activate so-vits-svc Then, install requirements. git clone https://github.com/svc-develop-team/so-vits-svc
cd so-vits-svc

pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

#for linux
pip install -r requirements.txt

#for windows
pip install -r requirements_win.txt
pip install --upgrade fastapi==0.84.0
pip install --upgrade gradio==3.41.2
pip install --upgrade pydantic==1.10.12
pip install fastapi uvicorn Initialization Download pre-trained models pre-train wget https://huggingface.co/WitchHuntTV/checkpoint_best_legacy_500.pt/resolve/main/checkpoint_best_legacy_500.pt wget https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/rmvpe.pt logs/44k wget https://huggingface.co/datasets/ms903/sovits4.0-768vec-layer12/resolve/main/sovits_768l12_pre_large_320k/clean_D_320000.pth wget https://huggingface.co/datasets/ms903/sovits4.0-768vec-layer12/resolve/main/sovits_768l12_pre_large_320k/clean_G_320000.pth logs/44k/diffusion wget https://huggingface.co/datasets/ms903/Diff-SVC-refactor-pre-trained-model/resolve/main/fix_pitch_add_vctk_600k/model_0.pt (Alternative) wget https://huggingface.co/datasets/ms903/DDSP-SVC-4.0/resolve/main/pre-trained-model/model_0.pt (Alternative) wget https://huggingface.co/datasets/ms903/Diff-SVC-refactor-pre-trained-model/blob/main/hubertsoft_fix_pitch_add_vctk_500k/model_0.pt pre-train/nsf_hifigan wget -P pretrain/ https://github.com/openvpi/vocoders/releases/download/nsf-hifigan-v1/nsf_hifigan_20221211.zip unzip -od pretrain/nsf_hifigan pretrain/nsf_hifigan_20221211.zip Dataset Preparation Put all Prepared audio.wav files into dataset_raw/character cd so-vits-svc
python resample.py --skip_loudnorm
python preprocess_flist_config.py --speech_encoder vec768l12 --vol_aug
python preprocess_hubert_f0.py --use_diff Edit Configs The file is located at configs/config.json : the frequency of printing log : the frequency of saving checkpoints : total steps : numbers of saved checkpoints, 0 for unlimited. : fp32 In my case, : the smaller the faster (rougher), the larger the slower (better). log interval eval interval epochs keep ckpts half_type batch_size Recommended batch_size per VRAM: 4=6G；6=8G；10=12G；14=16G；20=24G Keep default for configs/diffusion.yaml Training python cluster/train_cluster.py --gpu
python train_index.py -c configs/config.json
python train.py -c configs/config.json -m 44k
python train_diff.py -c configs/diffusion.yaml On training steps: Use to train the main model; usually, 20k-30k would be usable, and 50k and up would be good enough. This can take a few days depending on the GPU speed. train.py Feel free to stop it by , and it will be continued training by re-run anytime. ctrl+c python train.py -c configs/config.json -m 44k Use to train the diffusion model; training steps is recommended at 1/3 of the main model. train_diff.py Be aware of over-training. Use to monitor the plots to see if it goes flat. tensorboard --logdir=./logs/44k Change the from 0.0001 to 0.00005 if necessary. learning rate When done, share/transport these files for inference. config/ config.json diffusion.yaml logs/44k feature_and_index.pkl kmeans_10000.pt model_0.pt G_xxxxx.pt Inference It’s time to try out the trained model. I’d prefer Webui for the convenience of tweaking the parameters. But before firing it up, edit the following lines in for LAN access: webUI.py os.system("start http://localhost:7860")
app.launch(server_name="0.0.0.0", server_port=7860) Run ; then access its from a web browser. python webUI.py ipaddress:7860 The webui has no English localization, but would be helpful. Immersive Translate Most parameters would work well with the default value. Refer to and to make changes. this this Upload these 5 files: and its main model.pt config.json and its diffusion model.pt diffusion.yaml Either cluster model for speaking or feature retrieval for singing. kmeans_10000.pt feature_and_index.pkl is for speaking only, not for singing. Recommend when using. F0 predictor RMVPE is useful when singing a feminine song using a model with a masculine voice, or vice versa. Pitch change is the way of controlling the tone. Use to get the clearest speech, and use to get the closest tone to the model. Clustering model/feature retrieval mixing ratio 0.1 0.9 should be set around , it enhances the result at steps. shallow diffusion steps 50 30-100 Audio Editing This procedure is optional. Just for the production of a better song. I won’t go into details about this since the audio editing software, or so-called DAW (digital audio workstation), that I’m using is non-free. I have no intention to advocate proprietary software even though the entire industry is paywalled and closed-source. Audacity supports multitrack, effects, and a lot more. It does load some advanced VST plugins as well. It’s not hard to find tutorials on mastering songs with Audacity. Typically, the mastering process should be mixing/balancing, EQ/compressing, reverb, and imaging. The more advanced the tool is, the easier the process will be. I’ll definitely spend more time on adopting Audacity for my mastering process in the future, and I recommend everyone do so. so-vits-svc-fork This is a so-vits-svc with real-time support, and the models are compatible. Easier to use but does not support the Diffusion model. For dedicated real-time voice changing, a is recommended. fork voice-changer Installation conda create -n so-vits-svc-fork python=3.10 pip
conda activate so-vits-svc-fork

git clone https://github.com/voicepaw/so-vits-svc-fork
cd so-vits-svc-fork

python -m pip install -U pip setuptools wheel
pip install -U torch torchaudio --index-url https://download.pytorch.org/whl/cu118
pip install -U so-vits-svc-fork
pip install click
sudo apt-get install libportaudio2 Preparation Put dataset .wav files into so-vits-svc-fork/dataset_raw svc pre-resample
svc pre-config Edit a in . This fork is a larger size than the original. batch_size configs/44k/config.json Training svc pre-hubert
svc train -t
svc train-cluster Inference Use GUI with . This requires a local desktop environment. svcg Or use CLI with for real time and for generating. svc vc svc infer -m "logs/44k/xxxxx.pth" -c "configs/config.json" raw/xxx.wav DDSP-SVC requires fewer hardware resources and runs faster than so-vits-svc. It supports both real-time and diffusion models (Diff-SVC). DDSP-SVC conda create -n DDSP-SVC python=3.8
conda activate DDSP-SVC

git clone https://github.com/yxlllc/DDSP-SVC
cd DDSP-SVC

pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
pip install -r requirements.txt Refer to the for the two files: Initialization section pretrain/rmvpe/model.pt
pretrain/contentvec/checkpoint_best_legacy_500.pt Preparation python draw.py
python preprocess.py -c configs/combsub.yaml
python preprocess.py -c configs/diffusion-new.yaml Edit configs/ batch_size: 32  (16 for diffusion)
cache_all_data: false
cache_device: 'cuda'
cache_fp16: false Training conda activate DDSP-SVC
python train.py -c configs/combsub.yaml
python train_diff.py -c configs/diffusion-new.yaml

tensorboard --logdir=exp Inference It’s recommended to use since it includes both DDSP and diffusion model. main_diff.py python main_diff.py -i "input.wav" -diff "model_xxxxxx.pt" -o "output.wav" Real-time GUI for voice cloning: python gui_diff.py Bert-vits2-V2.3 This is a TTS tool that is completely different from everything above. By using it, I have already created several audiobooks with my voice for my parents, and they really enjoy it. Instead of using the , I used the fork by for an easier setup. original v3u Initialization conda create -n bert-vits2 python=3.9
conda activate bert-vits2

git clone https://github.com/v3ucn/Bert-vits2-V2.3.git
cd Bert-vits2-V2.3

pip install torch==2.0.1+cu118 torchvision==0.15.2+cu118 torchaudio==2.0.2+cu118 --index-url https://download.pytorch.org/whl/cu118
pip install -r requirements.txt Download pre-trained models (includes Chinese, Japanese, and English): wget -P slm/wavlm-base-plus/ https://huggingface.co/microsoft/wavlm-base-plus/resolve/main/pytorch_model.bin
wget -P emotional/clap-htsat-fused/ https://huggingface.co/laion/clap-htsat-fused/resolve/main/pytorch_model.bin
wget -P emotional/wav2vec2-large-robust-12-ft-emotion-msp-dim/ https://huggingface.co/audeering/wav2vec2-large-robust-12-ft-emotion-msp-dim/resolve/main/pytorch_model.bin
wget -P bert/chinese-roberta-wwm-ext-large/ https://huggingface.co/hfl/chinese-roberta-wwm-ext-large/resolve/main/pytorch_model.bin
wget -P bert/bert-base-japanese-v3/ https://huggingface.co/cl-tohoku/bert-base-japanese-v3/resolve/main/pytorch_model.bin
wget -P bert/deberta-v3-large/ https://huggingface.co/microsoft/deberta-v3-large/resolve/main/pytorch_model.bin
wget -P bert/deberta-v3-large/ https://huggingface.co/microsoft/deberta-v3-large/resolve/main/pytorch_model.generator.bin
wget -P bert/deberta-v2-large-japanese/ https://huggingface.co/ku-nlp/deberta-v2-large-japanese/resolve/main/pytorch_model.bin Create a character model folder mkdir -p Data/xxx/models/ Download base models: !wget -P Data/xxx/models/ https://huggingface.co/OedoSoldier/Bert-VITS2-2.3/resolve/main/DUR_0.pth
!wget -P Data/xxx/models/ https://huggingface.co/OedoSoldier/Bert-VITS2-2.3/resolve/main/D_0.pth
!wget -P Data/xxx/models/ https://huggingface.co/OedoSoldier/Bert-VITS2-2.3/resolve/main/G_0.pth
!wget -P Data/xxx/models/ https://huggingface.co/OedoSoldier/Bert-VITS2-2.3/resolve/main/WD_0.pth

#More options
https://openi.pcl.ac.cn/Stardust_minus/Bert-VITS2/modelmanage/model_filelist_tmpl?name=Bert-VITS2_2.3%E5%BA%95%E6%A8%A1
https://huggingface.co/Erythrocyte/bert-vits2_base_model/tree/main
https://huggingface.co/OedoSoldier/Bert-VITS2-2.3/tree/main Edit by replacing all to train_ms.py bfloat16 float16 Edit for LAN access: webui.py webbrowser.open(f"start http://localhost:7860")
app.launch(server_name="0.0.0.0", server_port=7860) Edit for and Data/xxx/config.json batch_size spk2id Preparation Similar workflow as in the . previous section Remove noise and silence, normalization, then put the un-sliced WAV file into . Data/xxx/raw Edit for , , and . config.yml dataset_path num_workers keep_ckpts Run to slice the WAV file. python3 audio_slicer.py Clean the dataset ( ) by removing small files that are under 2 sec. Data/xxx/raw Transcription Install whisper pip install git+https://github.com/openai/whisper.git To turn off language auto-detection, set it to English only, and use model; edit as below: large short_audio_transcribe.py # set the spoken language to english
    print('language: en')
    lang = 'en'
    options = whisper.DecodingOptions(language='en')
    result = whisper.decode(model, mel, options)
	
    # set to use large model
    parser.add_argument("--whisper_size", default="large")

    #Solve error "Given groups=1, weight of size [1280, 128, 3], expected input[1, 80, 3000] to have 128 channels, but got 80 channels instead" while using large model
    mel = whisper.log_mel_spectrogram(audio,n_mels = 128).to(model.device) Run to start the transcription. python3 short_audio_transcribe.py Re-sample the sliced dataset: python3 resample.py --sr 44100 --in_dir ./Data/zizek/raw/ --out_dir ./Data/zizek/wavs/ Preprocess transcription: python3 preprocess_text.py --transcription-path ./Data/zizek/esd.list Generate BERT feature config: python3 bert_gen.py --config-path ./Data/zizek/configs/config.json Training and Inference Run to start training python3 train_ms.py Edit for model path: config.yml model: "models/G_20900.pth" Run to start webui for inference python3 webui.py vits-simple-api is a web frontend for using trained models. I use this mainly for its long text support which the original project doesn’t have. vits-simple-api git clone https://github.com/Artrajz/vits-simple-api
git pull https://github.com/Artrajz/vits-simple-api
cd vits-simple-api

conda create -n vits-simple-api python=3.10 pip
conda activate vits-simple-api && 

pip install -r requirements.txt (Optional) Copy pre-trained model files from to Bert-vits2-V2.3/ vits-simple-api/bert_vits2/ Copy and to Bert-vits2-V2.3/Data/xxx/models/G_xxxxx.pth Bert-vits2-V2.3/Data/xxx/config.json vits-simple-api/Model/xxx/ Edit for and as preferred config.py MODEL_LIST Default parameter Edit as below: Model/xxx/config.json "data": {
    "training_files": "Data/train.list",
    "validation_files": "Data/val.list",
	
  "version": "2.3" Check/Edit in as model_list config.yml [xxx/G_xxxxx.pth, xxx/config.json] Run python app.py Tweaks for tone, for randomness, for pronunciation, and for speed. and are self-explanatory SDP Ratio Noise Noise_W Length emotion style Share Models In its , there are a lot of VITS models shared by others. You can try it out first, and then download the desired models from . Hugging Face repo Files The is widely used in some content creation communities because of its high quality. It contains hundreds of characters, although only Chinese and Japanese are supported. Genshin model In , there are a lot of Bert-vits2 models that are made from popular Chinese streamers and VTubers. another repo There are already projects making AI Vtubers like and . I’m looking forward to how this technology can change the industry in the near future. this this https://techshinobi.org/posts/voice-vits/https://techshinobi.org/posts/voice-vits/

How to Voice Clone With SoftVC VITS and Bert-VITS2: A Deep Dive

SoftVC VITS এবং Bert-VITS2 দিয়ে কীভাবে ভয়েস ক্লোন করবেন: একটি গভীর ডুব

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SoftVC VITS および Bert-VITS2 を使用して音声クローンを作成する方法: 詳細

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147 Stories To Learn About Reading Books Online

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