HF's ML for Audio study group

Overview

Hugging Face Machine Learning for Audio Study Group

Welcome to the ML for Audio Study Group. Through a series of presentations, paper reading and discussions, we'll explore the field of applying Machine Learning in the Audio domain. Some examples of this are:

  • Generating synthetic sound out of a given text (think of conversational assistants)
  • Transcribing audio signals to text.
  • Removing noise out of an audio.
  • Separating different sources of audio.
  • Identifying which speaker is talking.
  • And much more!

We suggest you to join the community Discord at http://hf.co/join/discord, and we're looking forward to meet at the #ml-4-audio-study-group channel 🤗 . Remember, this is a community effort so make out of this your space!

Organisation

We'll kick off with some basics and then collaboratively decide the further direction of the group.

Before each session:

  • Read/watch related resources

During each session, you can

  • Ask question in the forum
  • Present a short (~10-15mins) presentation on the topic (agree beforehand)

Before/after:

  • Keep discussing/asking questions about the topic (#ml-4-audio-study channel on discord)
  • Share interesting resources

Schedule

Date Topics Resources (To read before)
Dec 14, 2021 Kickoff + Overview of Audio related usecases (video, questions) The 3 DL Frameworks for e2e Speech Recognition that power your devices
Dec 21, 2021
  • Intro to Audio
  • Automatic Speech Recognition Deep Dive
(video, questions)
Jan 4, 2022 Text to Speech Deep Dive (video, questions)
Jan 18, 2022 pyctcdecode: A simple & fast STT prediction decoding algorithm (demo, slides, questions)

Supplementary Resources

In case you want to solidify a concept, or just want to go down further deep into the speech processing rabbit-hole.

General Resources

  • Slides from LSA352: Slides (no videos available)
  • Slides from CS224S (Latest): Slides (no videos available)
  • Speech & Language Processing Book (Chapters 25 & 26) - E-book

Research Papers

Toolkits

Demos

Owner
Vaibhav Srivastav
Tech Speaker | Computational Linguist | Consultant
Vaibhav Srivastav
Blender addon - Scrub timeline from viewport with a shortcut

Viewport scrub timeline Move in the timeline directly in viewport and snap to nearest keyframe Note : This standalone feature will be added in the nat

Samuel Bernou 40 Nov 07, 2022
The first online catalogue for Arabic NLP datasets.

Masader The first online catalogue for Arabic NLP datasets. This catalogue contains 200 datasets with more than 25 metadata annotations for each datas

ARBML 94 Dec 26, 2022
Concept Modeling: Topic Modeling on Images and Text

Concept is a technique that leverages CLIP and BERTopic-based techniques to perform Concept Modeling on images.

Maarten Grootendorst 120 Dec 27, 2022
A toolkit for document-level event extraction, containing some SOTA model implementations

Document-level Event Extraction via Heterogeneous Graph-based Interaction Model with a Tracker Source code for ACL-IJCNLP 2021 Long paper: Document-le

84 Dec 15, 2022
Simple GUI where you can enter an article and get a crisp summarized version.

Text-Summarization-using-TextRank-BART Simple GUI where you can enter an article and get a crisp summarized version. How to run: Clone the repo Instal

Rohit P 4 Sep 28, 2022
Japanese NLP Library

Japanese NLP Library Back to Home Contents 1 Requirements 1.1 Links 1.2 Install 1.3 History 2 Libraries and Modules 2.1 Tokenize jTokenize.py 2.2 Cabo

Pulkit Kathuria 144 Dec 27, 2022
Beyond Paragraphs: NLP for Long Sequences

Beyond Paragraphs: NLP for Long Sequences

AI2 338 Dec 02, 2022
NewsMTSC: (Multi-)Target-dependent Sentiment Classification in News Articles

NewsMTSC: (Multi-)Target-dependent Sentiment Classification in News Articles NewsMTSC is a dataset for target-dependent sentiment classification (TSC)

Felix Hamborg 79 Dec 30, 2022
This repo stores the codes for topic modeling on palliative care journals.

This repo stores the codes for topic modeling on palliative care journals. Data Preparation You first need to download the journal papers. bash 1_down

3 Dec 20, 2022
wxPython app for converting encodings, modifying and fixing SRT files

Subtitle Converter Program za obradu srt i txt fajlova. Requirements: Python version 3.8 wxPython version 4.1.0 or newer Libraries: srt, PyDispatcher

4 Nov 25, 2022
Textlesslib - Library for Textless Spoken Language Processing

textlesslib Textless NLP is an active area of research that aims to extend NLP t

Meta Research 379 Dec 27, 2022
Pretrained language model and its related optimization techniques developed by Huawei Noah's Ark Lab.

Pretrained Language Model This repository provides the latest pretrained language models and its related optimization techniques developed by Huawei N

HUAWEI Noah's Ark Lab 2.6k Jan 08, 2023
A Streamlit web app that generates Rick and Morty stories using GPT2.

Rick and Morty Story Generator This project uses a pre-trained GPT2 model, which was fine-tuned on Rick and Morty transcripts, to generate new stories

₸ornike 33 Oct 13, 2022
Task-based datasets, preprocessing, and evaluation for sequence models.

SeqIO: Task-based datasets, preprocessing, and evaluation for sequence models. SeqIO is a library for processing sequential data to be fed into downst

Google 290 Dec 26, 2022
LV-BERT: Exploiting Layer Variety for BERT (Findings of ACL 2021)

LV-BERT Introduction In this repo, we introduce LV-BERT by exploiting layer variety for BERT. For detailed description and experimental results, pleas

Weihao Yu 14 Aug 24, 2022
Synthetic data for the people.

zpy: Synthetic data in Blender. Website • Install • Docs • Examples • CLI • Contribute • Licence Abstract Collecting, labeling, and cleaning data for

Zumo Labs 253 Dec 21, 2022
Data and code to support "Applied Natural Language Processing" (INFO 256, Fall 2021, UC Berkeley)

anlp21 Course materials for "Applied Natural Language Processing" (INFO 256, Fall 2021, UC Berkeley) Syllabus: http://people.ischool.berkeley.edu/~dba

David Bamman 48 Dec 06, 2022
🗣️ NALP is a library that covers Natural Adversarial Language Processing.

NALP: Natural Adversarial Language Processing Welcome to NALP. Have you ever wanted to create natural text from raw sources? If yes, NALP is for you!

Gustavo Rosa 21 Aug 12, 2022
Natural language Understanding Toolkit

Natural language Understanding Toolkit TOC Requirements Installation Documentation CLSCL NER References Requirements To install nut you need: Python 2

Peter Prettenhofer 119 Oct 08, 2022
📜 GPT-2 Rhyming Limerick and Haiku models using data augmentation

Well-formed Limericks and Haikus with GPT2 📜 GPT-2 Rhyming Limerick and Haiku models using data augmentation In collaboration with Matthew Korahais &

Bardia Shahrestani 2 May 26, 2022