14 citations · 16 across the 10 of their papers we have counts for
11 papers
When Text Misleads: Inconsistent-Aware Reasoning for Audio-Grounded Dialogue
Yen-Ju Lu, Yuzhe Wang, Yaohan Guan +8
Understanding spoken dialogue requires joint reasoning over lexical content and paralinguistic acoustic signals such as emotion and conversational intent. However, existing evaluat…
StanceBench: A Benchmark for Audio LLM-Based Interpersonal Stance Evaluation from Speech
Yuzhe Wang, Thomas Thebaud, Jennifer Hu +5
Speech-to-speech dialogue models increasingly depend on prosody and interactional nuance to convey social intent, yet benchmarks for these cues remain limited. We introduce StanceB…
Beyond Transcripts: Iterative Peer-Editing with Audio Unlocks High-Quality Human Summaries of Conversational Speech
Kaavya Chaparala, Thomas Thebaud, Jesús Villalba López +3
There are not enough established benchmarks for the task fo speech summarization. Creating new benchmarks demands human annotation, as LLMs could embed systemic errors and bias int…
Layer-Aware Early Fusion of Acoustic and Linguistic Embeddings for Cognitive Status Classification
Krystof Novotny, Laureano Moro-Velázquez, Jiri Mekyska
Speech contains both acoustic and linguistic patterns that reflect cognitive decline, and therefore models describing only one domain cannot fully capture such complexity. This stu…
Self-FiLM: Conditioning GANs with self-supervised representations for bandwidth extension based speaker recognition
Saurabh Kataria, Jesús Villalba, Laureano Moro-Velázquez +2
Speech super-resolution/Bandwidth Extension (BWE) can improve downstream tasks like Automatic Speaker Verification (ASV). We introduce a simple novel technique called Self-FiLM to…
Time-domain speech super-resolution with GAN based modeling for telephony speaker verification
Saurabh Kataria, Jesús Villalba, Laureano Moro-Velázquez +2
Automatic Speaker Verification (ASV) technology has become commonplace in virtual assistants. However, its performance suffers when there is a mismatch between the train and test d…
Joint domain adaptation and speech bandwidth extension using time-domain GANs for speaker verification
Saurabh Kataria, Jesús Villalba, Laureano Moro-Velázquez +1
Speech systems developed for a particular choice of acoustic domain and sampling frequency do not translate easily to others. The usual practice is to learn domain adaptation and b…
Deep Feature CycleGANs: Speaker Identity Preserving Non-parallel Microphone-Telephone Domain Adaptation for Speaker Verification
Saurabh Kataria, Jesús Villalba, Piotr Żelasko +2
With the increase in the availability of speech from varied domains, it is imperative to use such out-of-domain data to improve existing speech systems. Domain adaptation is a prom…
Unsupervised Acoustic Unit Discovery by Leveraging a Language-Independent Subword Discriminative Feature Representation
Siyuan Feng, Piotr Żelasko, Laureano Moro-Velázquez +1
This paper tackles automatically discovering phone-like acoustic units (AUD) from unlabeled speech data. Past studies usually proposed single-step approaches. We propose a two-stag…
How Phonotactics Affect Multilingual and Zero-shot ASR Performance
Siyuan Feng, Piotr Żelasko, Laureano Moro-Velázquez +4
The idea of combining multiple languages' recordings to train a single automatic speech recognition (ASR) model brings the promise of the emergence of universal speech representati…
That Sounds Familiar: an Analysis of Phonetic Representations Transfer Across Languages
Piotr Żelasko, Laureano Moro-Velázquez, Mark Hasegawa-Johnson +2
Only a handful of the world's languages are abundant with the resources that enable practical applications of speech processing technologies. One of the methods to overcome this pr…