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References (25)

[1]
SepALM: Audio Language Models Are Error Correctors for Robust Speech Separation
2025Zhaoxi Mu, Xinyu Yang et al.
[2]
UniSep: Universal Target Audio Separation with Language Models at Scale
2025Yuanyuan Wang, Hangting Chen et al.
[3]
FireRedASR: Open-Source Industrial-Grade Mandarin Speech Recognition Models from Encoder-Decoder to LLM Integration
2025Kai-Tuo Xu, Fenglong Xie et al.
[4]
TSELM: Target Speaker Extraction using Discrete Tokens and Language Models
2024Beilong Tang, Bang Zeng et al.
[5]
Seed-ASR: Understanding Diverse Speech and Contexts with LLM-based Speech Recognition
2024Ye Bai, Jingping Chen et al.
[6]
Seed-TTS: A Family of High-Quality Versatile Speech Generation Models
2024Philip Anastassiou, Jiawei Chen et al.
[7]
SpeechBERTScore: Reference-Aware Automatic Evaluation of Speech Generation Leveraging NLP Evaluation Metrics
2024Takaaki Saeki, Soumi Maiti et al.
[8]
Cross-Speaker Encoding Network for Multi-Talker Speech Recognition
2024Jiawen Kang, Lingwei Meng et al.
[9]
SELM: Speech Enhancement using Discrete Tokens and Language Models
2023Ziqian Wang, Xinfa Zhu et al.
[10]
TokenSplit: Using Discrete Speech Representations for Direct, Refined, and Transcript-Conditioned Speech Separation and Recognition
2023Hakan Erdogan, Scott Wisdom et al.
[11]
SEPDIFF: Speech Separation Based on Denoising Diffusion Model
2023Bo-Cheng Chen, Chao Wu et al.
[12]
Adapting Multi-Lingual ASR Models for Handling Multiple Talkers
2023Chenda Li, Yao Qian et al.
[13]
Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers
2023Chengyi Wang, Sanyuan Chen et al.
[14]
Robust Speech Recognition via Large-Scale Weak Supervision
2022Alec Radford, Jong Wook Kim et al.
[15]
Diffusion-Based Generative Speech Source Separation
2022Robin Scheibler, Youna Ji et al.
[16]
High Fidelity Neural Audio Compression
2022Alexandre D'efossez, Jade Copet et al.
[17]
Music Source Separation With Band-Split RNN
2022Yi Luo, Jianwei Yu
[18]
WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing
2021Sanyuan Chen, Chengyi Wang et al.
[19]
SoundStream: An End-to-End Neural Audio Codec
2021Neil Zeghidour, Alejandro Luebs et al.
[20]
Attention Is All You Need In Speech Separation
2020Cem Subakan, M. Ravanelli et al.

Showing 20 of 25 references

Founder's Pitch

"Enhance speech intelligibility in separation tasks using speech language models for improved downstream task performance."

Speech TechnologyScore: 6View PDF ↗

Commercial Viability Breakdown

0-10 scale

High Potential

1/4 signals

2.5

Quick Build

4/4 signals

10

Series A Potential

1/4 signals

2.5

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