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Speech Tokenization

Speech tokenization is the task of representing speech signals as a sequence of discrete units. Such representations can be later used for various downstream tasks including automatic speech recognition, text-to-speech, etc. Such representation serves as the basis of Speech Language Models.

Papers

Showing 110 of 21 papers

TitleStatusHype
Sylber: Syllabic Embedding Representation of Speech from Raw AudioCode2
DM-Codec: Distilling Multimodal Representations for Speech TokenizationCode2
TASTE: Text-Aligned Speech Tokenization and Embedding for Spoken Language ModelingCode2
SyllableLM: Learning Coarse Semantic Units for Speech Language ModelsCode2
dMel: Speech Tokenization made SimpleCode1
Audio Jailbreak Attacks: Exposing Vulnerabilities in SpeechGPT in a White-Box FrameworkCode1
Self-Supervised Syllable Discovery Based on Speaker-Disentangled HuBERTCode1
RepCodec: A Speech Representation Codec for Speech TokenizationCode1
BEST-STD: Bidirectional Mamba-Enhanced Speech Tokenization for Spoken Term DetectionCode0
Impact of Frame Rates on Speech Tokenizer: A Case Study on Mandarin and English0
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