activity
20222026
most citedEmphasized Non-Target Speaker Knowledge in Knowledge Distillation for Automatic Speaker Verification

12 citations · 22 across the 23 of their papers we have counts for

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Showing 2024Show all

8 papers · 1 filter

cs.SD2024

VERSA: A Versatile Evaluation Toolkit for Speech, Audio, and Music

Jiatong Shi, Hye-jin Shim, Jinchuan Tian +14

In this work, we introduce VERSA, a unified and standardized evaluation toolkit designed for various speech, audio, and music signals. The toolkit features a Pythonic interface wit…

eess.AS2024★ 1 cited

Speech Separation using Neural Audio Codecs with Embedding Loss

Jia Qi Yip, Chin Yuen Kwok, Bin Ma +1

Neural audio codecs have revolutionized audio processing by enabling speech tasks to be performed on highly compressed representations. Recent work has shown that speech separation…

cs.CL2024

Dynamic-SUPERB Phase-2: A Collaboratively Expanding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 Tasks

Chien-yu Huang, Wei-Chih Chen, Shu-wen Yang +77

Multimodal foundation models, such as Gemini and ChatGPT, have revolutionized human-machine interactions by seamlessly integrating various forms of data. Developing a universal spo…

eess.AS2024

Emotional Dimension Control in Language Model-Based Text-to-Speech: Spanning a Broad Spectrum of Human Emotions

Kun Zhou, You Zhang, Dianwen Ng +3

Emotional text-to-speech (TTS) systems sturggle to capture the full spectrum of human emotions due to the inherent complexity of emotional expressions and the limited coverage of e…

eess.AS2024

ESPnet-Codec: Comprehensive Training and Evaluation of Neural Codecs for Audio, Music, and Speech

Jiatong Shi, Jinchuan Tian, Yihan Wu +17

Neural codecs have become crucial to recent speech and audio generation research. In addition to signal compression capabilities, discrete codecs have also been found to enhance do…

cs.SD2024

Towards Audio Codec-based Speech Separation

Jia Qi Yip, Shengkui Zhao, Dianwen Ng +2

Recent improvements in neural audio codec (NAC) models have generated interest in adopting pre-trained codecs for a variety of speech processing applications to take advantage of t…

cs.CL2024★ 4 cited

Continual Learning Optimizations for Auto-regressive Decoder of Multilingual ASR systems

Chin Yuen Kwok, Jia Qi Yip, Eng Siong Chng

Continual Learning (CL) involves fine-tuning pre-trained models with new data while maintaining the performance on the pre-trained data. This is particularly relevant for expanding…

eess.AS2024

Phonetic Enhanced Language Modeling for Text-to-Speech Synthesis

Kun Zhou, Shengkui Zhao, Yukun Ma +7

Recent language model-based text-to-speech (TTS) frameworks demonstrate scalability and in-context learning capabilities. However, they suffer from robustness issues due to the acc…