18 citations · 26 across the 35 of their papers we have counts for
10 papers · 1 filter
MP-Bench: Evaluating Voice Agents as a Multiparty Conversation Participant
Yi-Jen Shih, Shih-Yun Shan Kuan, Guan-Ting Lin +7
Conversational voice agents have advanced significantly, offering increasingly natural human-machine interactions through both cascaded and end-to-end architectures. However, while…
An Efficient vLLM-Based Inference Pipeline for Unified Audio Understanding and Generation
Haoran Wang, Jinchuan Tian, Siddhant Arora +1
While Large Multimodal Models excel in comprehension, high-throughput inference engines lack native support for multimodal generation. This is severe in Speech Language Models, whe…
ESPnet3: Infrastructure for Scalable Speech and Audio Research in the Foundation Model Era
Masao Someki, Alexander Polok, Carlos Carvalho +14
Recent speech research involves increasingly large datasets, complex models, and diverse experimental workflows. However, existing frameworks require substantial engineering effort…
Full-Duplex-Bench-v2: A Multi-Turn Evaluation Framework for Duplex Dialogue Systems with an Automated Examiner
Guan-Ting Lin, Shih-Yun Shan Kuan, Jiatong Shi +4
While full-duplex speech agents enable natural, low-latency interaction by speaking and listening simultaneously, their consistency and task performance in multi-turn settings rema…
Spiralformer: Low Latency Encoder for Streaming Speech Recognition with Circular Layer Skipping and Early Exiting
Emiru Tsunoo, Hayato Futami, Yosuke Kashiwagi +2
For streaming speech recognition, a Transformer-based encoder has been widely used with block processing. Although many studies addressed improving emission latency of transducers,…
SIFT-50M: A Large-Scale Multilingual Dataset for Speech Instruction Fine-Tuning
Prabhat Pandey, Rupak Vignesh Swaminathan, K V Vijay Girish +4
We introduce SIFT (Speech Instruction Fine-Tuning), a 50M-example dataset designed for instruction fine-tuning and pre-training of speech-text large language models (LLMs). SIFT-50…