activity
20232026
most citedImproving Code-Switching and Named Entity Recognition in ASR with Speech Editing based Data Augmentation

4 citations · 9 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SD2026

MMAE: A Massive Multitask Audio Editing Benchmark

Ziyang Ma, Ruiqi Yan, Ruiyang Xu +35

We introduce MMAE, a Massive Multitask Audio Editing benchmark, serving as the first comprehensive evaluation testbed designed for general-purpose instruction-based audio editing.…

cs.SD2026★ 3 cited

SLAM-LLM: A Modular, Open-Source Multimodal Large Language Model Framework and Best Practice for Speech, Language, Audio and Music Processing

Ziyang Ma, Guanrou Yang, Wenxi Chen +19

The recent surge in open-source Multimodal Large Language Models (MLLM) frameworks, such as LLaVA, provides a convenient kickoff for artificial intelligence developers and research…

cs.AI2024

A Comparative Study of LLM-based ASR and Whisper in Low Resource and Code Switching Scenario

Zheshu Song, Ziyang Ma, Yifan Yang +2

Large Language Models (LLMs) have showcased exceptional performance across diverse NLP tasks, and their integration with speech encoder is rapidly emerging as a dominant trend in t…

eess.AS2024

LoRA-Whisper: Parameter-Efficient and Extensible Multilingual ASR

Zheshu Song, Jianheng Zhuo, Yifan Yang +3

Recent years have witnessed significant progress in multilingual automatic speech recognition (ASR), driven by the emergence of end-to-end (E2E) models and the scaling of multiling…

eess.AS2024★ 2 cited

GigaSpeech 2: An Evolving, Large-Scale and Multi-domain ASR Corpus for Low-Resource Languages with Automated Crawling, Transcription and Refinement

Yifan Yang, Zheshu Song, Jianheng Zhuo +13

The evolution of speech technology has been spurred by the rapid increase in dataset sizes. Traditional speech models generally depend on a large amount of labeled training data, w…

cs.CL2023★ 4 cited

Improving Code-Switching and Named Entity Recognition in ASR with Speech Editing based Data Augmentation

Zheng Liang, Zheshu Song, Ziyang Ma +3

Recently, end-to-end (E2E) automatic speech recognition (ASR) models have made great strides and exhibit excellent performance in general speech recognition. However, there remain…