activity
20192026
most citedA Survey on Graph Neural Networks for Knowledge Graph Completion

18 citations · 47 across the 61 of their papers we have counts for

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Showing 2025Show all

16 papers · 1 filter

cs.CL2025

Chain-of-Thought Reasoning in Streaming Full-Duplex End-to-End Spoken Dialogue Systems

Siddhant Arora, Jinchuan Tian, Hayato Futami +4

Most end-to-end (E2E) spoken dialogue systems (SDS) rely on voice activity detection (VAD) for turn-taking, but VAD fails to distinguish between pauses and turn completions. Duplex…

cs.CL2025

Stream RAG: Instant and Accurate Spoken Dialogue Systems with Streaming Tool Usage

Siddhant Arora, Haidar Khan, Kai Sun +14

End-to-end speech-in speech-out dialogue systems are emerging as a powerful alternative to traditional ASR-LLM-TTS pipelines, generating more natural, expressive responses with sig…

eess.AS2025

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…

eess.AS2025

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,…

cs.LG2025

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…

cs.AI2025★ 1 cited

AURA: Agent for Understanding, Reasoning, and Automated Tool Use in Voice-Driven Tasks

Leander Melroy Maben, Gayathri Ganesh Lakshmy, Srijith Radhakrishnan +2

Despite advances in language and speech technologies, no open-source system enables full speech-to-speech, multi-turn dialogue with integrated tool use and agentic reasoning. We in…

cs.CL2025

OpusLM: A Family of Open Unified Speech Language Models

Jinchuan Tian, William Chen, Yifan Peng +9

This paper presents Open Unified Speech Language Models (OpusLMs), a family of open foundational speech language models (SpeechLMs) up to 7B. Initialized from decoder-only text lan…

cs.CL2025

Scheduled Interleaved Speech-Text Training for Speech-to-Speech Translation with LLMs

Hayato Futami, Emiru Tsunoo, Yosuke Kashiwagi +4

Speech-to-speech translation (S2ST) has been advanced with large language models (LLMs), which are fine-tuned on discrete speech units. In such approaches, modality adaptation from…

cs.CL2025

Chain-of-Thought Training for Open E2E Spoken Dialogue Systems

Siddhant Arora, Jinchuan Tian, Hayato Futami +5

Unlike traditional cascaded pipelines, end-to-end (E2E) spoken dialogue systems preserve full differentiability and capture non-phonemic information, making them well-suited for mo…

cs.AI2025★ 1 cited

BLAB: Brutally Long Audio Bench

Orevaoghene Ahia, Martijn Bartelds, Kabir Ahuja +13

Developing large audio language models (LMs) capable of understanding diverse spoken interactions is essential for accommodating the multimodal nature of human communication and ca…

cs.SD2025

ARECHO: Autoregressive Evaluation via Chain-Based Hypothesis Optimization for Speech Multi-Metric Estimation

Jiatong Shi, Yifan Cheng, Bo-Hao Su +6

Speech signal analysis poses significant challenges, particularly in tasks such as speech quality evaluation and profiling, where the goal is to predict multiple perceptual and obj…

eess.AS2025

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…

cs.CL2025★ 3 cited

On The Landscape of Spoken Language Models: A Comprehensive Survey

Siddhant Arora, Kai-Wei Chang, Chung-Ming Chien +7

The field of spoken language processing is undergoing a shift from training custom-built, task-specific models toward using and optimizing spoken language models (SLMs) which act a…

cs.CL2025

ESPnet-SDS: Unified Toolkit and Demo for Spoken Dialogue Systems

Siddhant Arora, Yifan Peng, Jiatong Shi +9

Advancements in audio foundation models (FMs) have fueled interest in end-to-end (E2E) spoken dialogue systems, but different web interfaces for each system makes it challenging to…

cs.CL2025★ 1 cited

Talking Turns: Benchmarking Audio Foundation Models on Turn-Taking Dynamics

Siddhant Arora, Zhiyun Lu, Chung-Cheng Chiu +2

The recent wave of audio foundation models (FMs) could provide new capabilities for conversational modeling. However, there have been limited efforts to evaluate these audio FMs co…

cs.CL2025★ 1 cited

ESPnet-SpeechLM: An Open Speech Language Model Toolkit

Jinchuan Tian, Jiatong Shi, William Chen +13

We present ESPnet-SpeechLM, an open toolkit designed to democratize the development of speech language models (SpeechLMs) and voice-driven agentic applications. The toolkit standar…