Data Science by ODS.ai 🦜
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First Telegram Data Science channel. Covering all technical and popular staff about anything related to Data Science: AI, Big Data, Machine Learning, Statistics, general Math and the applications of former. To reach editors contact: @malev
加ε…₯钑道
πŸ”₯Quasi-Breaking: An Algorithm Inks a Record Deal With Warner Music

Endel uses machine learning to create personalized tracks meant to help people focus, relax and sleep better by inputting factors such as heart rate, time of day, location and weather.
Looking forward to actual music-generating algorithm being signed up for label.

Link: https://hypebeast.com/2019/3/endel-algorithm-record-deal-warner-music

#MLHype #audiolearning #DL #Endel
πŸ”₯Singing voice conversion system developed at FAIR-Tel Aviv.

This can transform someone's singing voice into someone else's voice.

YouTube: https://www.youtube.com/watch?v=IEpkGenLnjw
Link: https://venturebeat.com/2019/04/16/facebooks-ai-can-convert-one-singers-voice-into-another/
ArXiV: https://arxiv.org/abs/1904.06590

#voiceconversion #audiolearning #DL #Facebook
Speech synthesis from neural decoding of spoken sentences

Researchers tapped the brains of five epilepsy patients who had been implanted with electrodes to map the source of seizures, according to a paper published by #Nature. During a lull in the procedure, they had the patients read English-language texts aloud. They recorded the fluctuating voltage as the brain controlled the muscles involved in speaking. Later, they fed the voltage measurements into a synthesizer.

Nature: https://www.nature.com/articles/s41586-019-1119-1
Paper: https://www.biorxiv.org/content/biorxiv/early/2018/11/29/481267.full.pdf
YouTube: https://www.youtube.com/watch?v=kbX9FLJ6WKw

#DeepDiveWeekly #DL #speech #audiolearning
​​Recovering person appereance from person’s speech

As the result of the research, much resembling facial image of a person reconstructed from short audio recording of that person speaking.

ArXiV: https://arxiv.org/pdf/1905.09773v1.pdf

#speech #audiolearning #CV #DL #face
​​Online speech recognition with wav2letter@anywhere

Facebook have open-sourced wav2letter@anywhere, an inference framework for online speech recognition that delivers state-of-the-art performance.

Link: https://ai.facebook.com/blog/online-speech-recognition-with-wav2letteranywhere/

#wav2letter #audiolearning #soundlearning #sound #acoustic #audio #facebook
​​Racial Disparities in Automated Speech Recognition

To no surprise, speech recognition tools have #bias due to the lack of diversity in the datasets. Group of explorers addressed that issue and provided their’s research results as a paper and #reproducible research repo.

Project link: https://fairspeech.stanford.edu
Paper: https://www.pnas.org/cgi/doi/10.1073/pnas.1915768117
Github: https://github.com/stanford-policylab/asr-disparities

#speechrecognition #voice #audiolearning #dl #microsoft #google #apple #ibm #amazon
β€‹β€‹πŸŽ™πŸŽΆImproved audio generative model from OpenAI

Wow! OpenAI just released Jukebox – neural net and service that generates music from genre, artist name, and some lyrics that you can supply. It is can generate even some singing like from corrupted magnet compact cassette.

Some of the sounds seem it is from hell. Agonizing Michel Jakson for example or Creepy Eminiem or Celien Dion

#OpenAI 's approach is to use 3 levels of quantized variational autoencoders VQVAE-2 to learn discrete representations of audio and compress audio by 8x, 32x, and 128x and use the spectral loss to reconstruct spectrograms. And after that, they use sparse transformers conditioned on lyrics to generate new patterns and upsample it to higher discrete samples and decode it to the song.

The net can even learn and generates some solo parts during the track.

explore some creepy songs: https://jukebox.openai.com/
code: https://github.com/openai/jukebox/
paper: https://cdn.openai.com/papers/jukebox.pdf
blog: https://openai.com/blog/jukebox/

#openAI #music #sound #cool #fan #creepy #vae #audiolearning #soundlearning
S2IGAN β€” Speech-to-Image Generation via Adversarial Learning

Authors present a framework that translates speech to images bypassing text information, thus allowing unwritten languages to potentially benefit from this technology.

ArXiV: https://arxiv.org/abs/2005.06968
Project: https://xinshengwang.github.io/project/s2igan/

#DL #audiolearning #speechrecognition