An open source implementation of Microsoft's VALL-E X zero-shot TTS model. Demo is available in https://plachtaa.github.io/vallex/
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Updated
Feb 11, 2024 - Python
An open source implementation of Microsoft's VALL-E X zero-shot TTS model. Demo is available in https://plachtaa.github.io/vallex/
😎 Awesome lists about Speech Emotion Recognition
Zero-shot voice cloning text-to-speech (TTS) with explicit emotion class conditioning built on F5-TTS
EmoTa is an open-access Tamil Speech Emotion Recognition dataset with 936 utterances from 22 native speakers, covering five emotions (anger, happiness, sadness, fear, and neutrality). It supports emotion classification tasks and advances Tamil language processing.
A modification on the Sharif Emotional Speech Database
ZET-Speech: Zero-shot adaptive Emotion-controllable Text-to-Speech Synthesis with Diffusion and Style-based Models (TTS)
Official GitHub page of E3-VITS
🎙️ German TTS (FastPitch) with Thorsten voice / emotional
EMOLIPS: TWO-LEVEL APPROACH FOR LIP-READING EMOTIONAL SPEECH
Applying deep learning to translate animation and re-generate audio.
An extensive collection of Speech Emotion Recognition (SER) datasets across multiple languages, including English, Mandarin, Hindi, Spanish, Tamil, Arabic, and more. Perfect for training emotion detection models in diverse linguistic and cultural contexts.
A GUI program for chat with chatbot such as chatgpt.
Multilingual emotional speech datasets for TTS training
Edison AT is AI emotional depression program. Developed using Python.
Fourteen speaker-verification encoders on identical trials under expressive speech: EER spans 0.047-0.233 on the same audio. Score tables, analysis code, and ten retracted claims. Paper: 10.5281/zenodo.22158030
This is a project dedicated to the classification of emotional speech and was created in class with Prof. Dr. Burkhardt at Technische Universität Berlin.
Explore the Transformer and DeepSeek V4.1 Flash in interactive 3D, with guided tours and component-level breakdowns.
This is a project dedicated to the classification of emotional speech and was created in class with Prof. Dr. Burkhardt at Technische Universität Berlin.
To associate your repository with the emotional-speech topic, visit your repo's landing page and select "manage topics."