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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 1120 of 21 papers

TitleStatusHype
DM-Codec: Distilling Multimodal Representations for Speech TokenizationCode2
Sylber: Syllabic Embedding Representation of Speech from Raw AudioCode2
SyllableLM: Learning Coarse Semantic Units for Speech Language ModelsCode2
Self-Supervised Syllable Discovery Based on Speaker-Disentangled HuBERTCode1
LAST: Language Model Aware Speech Tokenization0
STAB: Speech Tokenizer Assessment Benchmark0
dMel: Speech Tokenization made SimpleCode1
Discrete Multimodal Transformers with a Pretrained Large Language Model for Mixed-Supervision Speech Processing0
Scaling Properties of Speech Language Models0
BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data0
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