2 citations · 2 across the 14 of their papers we have counts for
14 papers
AURA: Uncertainty-Routed Activation Editing for Acoustic Grounding in Speech Foundation Models
Natarajan Balaji Shankar, Zilai Wang, Zihan Wang +3
Attention encoder-decoder (AED) Speech Foundation Models achieve strong ASR performance but can generate acoustically unsupported text when inputs contain no speech, weak acoustic…
Gumbel-BEARD: Automatic Layer Selection for Self-Supervised Adaptation of Whisper in Low-Resource Domains
Zilai Wang, Natarajan Balaji Shankar, Mohan Shi +2
Speech foundation models often struggle in low-resource domains due to domain mismatch and data scarcity. We propose Gumbel-BEARD, a domain adaptation framework that automates Whis…
GC-LoRA: Gated Convolutional LoRA for Parameter-Efficient Acoustic Adaptation
Natarajan Balaji Shankar, Zilai Wang, Kaiyuan Zhang +2
Transformer-based Speech Foundation Models excel in most Automatic Speech Recognition tasks but often suffer performance degradation when applied to domains with mismatched acousti…
Entropy-Aware Domain-Routed Mixture-of-Experts Speech-LLM Framework: A Case Study of Multi-Domain Child-Adult ASR
Mohan Shi, Kaiyuan Zhang, Zilai Wang +3
While Speech Large Language Models (Speech-LLMs) have achieved strong performance on adult Automatic Speech Recognition (ASR), their effectiveness on child speech remains under-exp…
STACodec: Semantic Token Assignment for Balancing Acoustic Fidelity and Semantic Information in Audio Codecs
Kaiyuan Zhang, Mohan Shi, Eray Eren +3
Neural audio codecs are widely used for audio compression and can be integrated into token-based language models. Traditional codecs preserve acoustic details well but lack semanti…
Mind the Shift: Using Delta SSL Embeddings to Enhance Child ASR
Zilai Wang, Natarajan Balaji Shankar, Kaiyuan Zhang +2
Self-supervised learning (SSL) models have achieved impressive results across many speech tasks, yet child automatic speech recognition (ASR) remains challenging due to limited dat…
Comparing Unsupervised and Supervised Semantic Speech Tokens: A Case Study of Child ASR
Mohan Shi, Natarajan Balaji Shankar, Kaiyuan Zhang +2
Discrete speech tokens have gained attention for their storage efficiency and integration with Large Language Models (LLMs). They are commonly categorized into acoustic and semanti…
Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet
Anyu Ying, Natarajan Balaji Shankar, Chyi-Jiunn Lin +7
Despite advancements in ASR, child speech recognition remains challenging due to acoustic variability and limited annotated data. While fine-tuning adult ASR models on child speech…
An Age-Agnostic System for Robust Speaker Verification
Jiusi Zheng, Vishwas Shetty, Natarajan Balaji Shankar +1
In speaker verification (SV), the acoustic mismatch between children's and adults' speech leads to suboptimal performance when adult-trained SV systems are applied to children's sp…
CHSER: A Dataset and Case Study on Generative Speech Error Correction for Child ASR
Natarajan Balaji Shankar, Zilai Wang, Kaiyuan Zhang +2
Automatic Speech Recognition (ASR) systems struggle with child speech due to its distinct acoustic and linguistic variability and limited availability of child speech datasets, lea…
Selective Attention Merging for low resource tasks: A case study of Child ASR
Natarajan Balaji Shankar, Zilai Wang, Eray Eren +1
While Speech Foundation Models (SFMs) excel in various speech tasks, their performance for low-resource tasks such as child Automatic Speech Recognition (ASR) is hampered by limite…
SOA: Reducing Domain Mismatch in SSL Pipeline by Speech Only Adaptation for Low Resource ASR
Natarajan Balaji Shankar, Ruchao Fan, Abeer Alwan
Recently, speech foundation models have gained popularity due to their superiority in finetuning downstream ASR tasks. However, models finetuned on certain domains, such as LibriSp…
Benchmarking Children's ASR with Supervised and Self-supervised Speech Foundation Models
Ruchao Fan, Natarajan Balaji Shankar, Abeer Alwan
Speech foundation models (SFMs) have achieved state-of-the-art results for various speech tasks in supervised (e.g. Whisper) or self-supervised systems (e.g. WavLM). However, the p…
UniEnc-CASSNAT: An Encoder-only Non-autoregressive ASR for Speech SSL Models
Ruchao Fan, Natarajan Balaji Shanka, Abeer Alwan
Non-autoregressive automatic speech recognition (NASR) models have gained attention due to their parallelism and fast inference. The encoder-based NASR, e.g. connectionist temporal…