1 citations · 1 across the 7 of their papers we have counts for
7 papers · 1 filter
Louder, Longer, Livelier: Acoustic Shortcuts and Underspecified Rationales in Speech LLM Judges
Mingyue Huo, Shivam Mehta, Bhavin Jawade +2
LLM-as-a-judge is widely used for evaluating text, but extending this paradigm to speech requires models to interpret acoustic as well as linguistic evidence. This introduces a mod…
Where Speech Enhancement Hurts Recognition: An Inference Time Polar Projection Diagnosis
Mingyue Huo, Yuheng Zhang, Hao Zhang
Speech enhancement (SE) can substantially improve perceptual quality, yet enhanced speech does not necessarily improve automatic speech recognition (ASR). Common explanations such…
TagSpeech: End-to-End Multi-Speaker ASR and Diarization with Fine-Grained Temporal Grounding
Mingyue Huo, Yiwen Shao, Yuheng Zhang
We present TagSpeech, a unified LLM-based framework that utilizes Temporal Anchor Grounding for joint multi-speaker ASR and diarization. The framework is built on two key designs:…
Auden-Voice: General-Purpose Voice Encoder for Speech and Language Understanding
Mingyue Huo, Wei-Cheng Tseng, Yiwen Shao +2
Human voice encodes both identity and paralinguistic cues, yet encoders in large audio-language models (LALMs) rarely balance both aspects. In this work, we present a study toward…
Revisiting Audio-language Pretraining for Learning General-purpose Audio Representation
Wei-Cheng Tseng, Xuanru Zhou, Mingyue Huo +3
Audio-language pretraining (ALP) holds promise for learning general-purpose audio representation, yet remains underexplored. Crucially, there is no consensus on whether audio-langu…
Identifying and Calibrating Overconfidence in Noisy Speech Recognition
Mingyue Huo, Yuheng Zhang, Yan Tang
Modern end-to-end automatic speech recognition (ASR) models like Whisper not only suffer from reduced recognition accuracy in noise, but also exhibit overconfidence - assigning hig…
Beyond Speaker Identity: Text Guided Target Speech Extraction
Mingyue Huo, Abhinav Jain, Cong Phuoc Huynh +4
Target Speech Extraction (TSE) traditionally relies on explicit clues about the speaker's identity like enrollment audio, face images, or videos, which may not always be available.…