feature extraction from speech signals

Praat: Doing Phonetics By Computer

INTERSPEECH 2023 Papers: A complete collection of influential and exciting research papers from the INTERSPEECH 2023 conference. Explore the latest advances in speech and language processing. Code included. Star the repository to support the advancement of speech technology!

Introduction to Speech Processing

An hate speech detection built from scratch with NLTK, WordCloud, and word_tokenize.

The SpeechBrain project aims to build a novel speech toolkit fully based on PyTorch. With SpeechBrain users can easily create speech processing systems, ranging from speech recognition (both HMM/DNN and end-to-end), speaker recognition, speech enhancement, speech separation, multi-microphone speech processing, and many others.

An opensource harmonizer implementation leveraging the DISTRHO Plugin Framework.

Language data store and linguistic query API

2-People-New-Zealand-English-Average-Tone-Speech-Synthesis-Corpus

AI powered ytp/sentence mixing for audio and video.

General Speech Restoration

Vowel formant frequency synthesis and analysis on the browser -- https://hlorenzi.github.io/vowel-analysis/

A sound cloning tool with a web interface, using your voice or any sound to record audio / 一个带web界面的声音克隆工具，使用你的音色或任意声音来录制音频

👩🏿‍💻IIIT Hyderabad Reasearch Teaser Programme : We developed a robust emotion😃 recognition system utilizing machine learning techniques on the 🗣️CREMA-D dataset to classify various emotions expressed in audio recordings🎙️ accurately.

Acoustic-prosodic entrainment measurement in spoken dialogue and approximation of the evolution of a speaker’s a/p features.

This project was done as part of a research teaser project on Speaker Recognition conducted with IIIT Hydrabad.

This repository houses a robust speech emotion recognition system, featuring signal processing scripts, machine learning algorithms, and comprehensive documentation. It accurately classifies emotions in spoken language, enabling applications like sentiment analysis and emotion-aware systems.

General Speech Restoration

In this project, the performance of speech emotion recognition is compared between two methods (SVM vs Bi-LSTM RNN).Conventional classifiers that uses machine learning algorithms has been used for decades in recognizing emotions from speech. However, in recent years, deep learning methods have taken the center stage and have gained popularity fo…

DynamicFluency - Monitor and understand the dynamicity of linguistic aspects in (L2) speech