NISQA - Non-Intrusive Speech Quality and TTS Naturalness Assessment
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Updated
Dec 1, 2024 - Python
NISQA - Non-Intrusive Speech Quality and TTS Naturalness Assessment
The repository provides links to collections of influential and interesting research papers from top AI conferences, with open-source code to promote reproducibility and provide detailed implementation insights beyond the scope of the article. Stay up to date with the latest advances in AI research!
[InterSpeech 24] FreeV: Free Lunch For Vocoders Through Pseudo Inversed Mel Filter
a deep accent recognition network
Supplementary information and code for INTERSPEECH 2018 paper: Singing voice phoneme segmentation by hierarchically inferring syllable and phoneme onset positions
PHO-LID: A Unified Model to Incorporate Acoustic-Phonetic and Phonotactic Information for Language Identification
This repository is the implementation of the paper, "Score-balanced Loss for Multi-aspect Pronunciation Assessment" (Interspeech 2023).
Interspeech 2019 experiments
The implementation code for the paper "Gate Activation Signal Analysis for Gated Recurrent Neural Networks and Its Correlation with Phoneme Boundaries"
Code-Switching Sentence Generation by Generative Adversarial Networks and its Application to Data Augmentation. (Interspeech 2019)
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