2 citations · 2 across the 6 of their papers we have counts for
6 papers
Fixed Anchors Are Not Enough: Dynamic Retrieval and Persistent Homology for Dataset Distillation
Muquan Li, Hang Gou, Yingyi Ma +3
Decoupled dataset distillation (DD) compresses large corpora into a few synthetic images by matching a frozen teacher's statistics. However, current residual-matching pipelines rel…
Transducer-Llama: Integrating LLMs into Streamable Transducer-based Speech Recognition
Keqi Deng, Jinxi Guo, Yingyi Ma +4
While large language models (LLMs) have been applied to automatic speech recognition (ASR), the task of making the model streamable remains a challenge. This paper proposes a novel…
Effective Text Adaptation for LLM-based ASR through Soft Prompt Fine-Tuning
Yingyi Ma, Zhe Liu, Ozlem Kalinli
The advent of Large Language Models (LLM) has reformed the Automatic Speech Recognition (ASR). Prompting LLM with audio embeddings to generate transcriptions becomes the new state-…
Effective internal language model training and fusion for factorized transducer model
Jinxi Guo, Niko Moritz, Yingyi Ma +6
The internal language model (ILM) of the neural transducer has been widely studied. In most prior work, it is mainly used for estimating the ILM score and is subsequently subtracte…
Correction Focused Language Model Training for Speech Recognition
Yingyi Ma, Zhe Liu, Ozlem Kalinli
Language models (LMs) have been commonly adopted to boost the performance of automatic speech recognition (ASR) particularly in domain adaptation tasks. Conventional way of LM trai…
Contextual Biasing of Named-Entities with Large Language Models
Chuanneng Sun, Zeeshan Ahmed, Yingyi Ma +4
This paper studies contextual biasing with Large Language Models (LLMs), where during second-pass rescoring additional contextual information is provided to a LLM to boost Automati…