Search Results for author:
Found 32 papers, 8 papers with code
PHRASED: Phrase Dictionary Biasing for Speech Translation
We apply the phrase dictionary biasing method to two types of widely adopted models, a transducer-based streaming speech translation model and a multimodal large language model.
AnnaAgent: Dynamic Evolution Agent System with Multi-Session Memory for Realistic Seeker Simulation
Constrained by the cost and ethical concerns of involving real seekers in AI-driven mental health, researchers develop LLM-based conversational agents (CAs) with tailored configurations, such as profiles, symptoms, and scenarios, to simulate seekers.
TeleAntiFraud-28k: An Audio-Text Slow-Thinking Dataset for Telecom Fraud Detection
The detection of telecom fraud faces significant challenges due to the lack of high-quality multimodal training data that integrates audio signals with reasoning-oriented textual analysis.
SARChat-Bench-2M: A Multi-Task Vision-Language Benchmark for SAR Image Interpretation
As a powerful all-weather Earth observation tool, synthetic aperture radar (SAR) remote sensing enables critical military reconnaissance, maritime surveillance, and infrastructure monitoring.
Streaming Speaker Change Detection and Gender Classification for Transducer-Based Multi-Talker Speech Translation
We propose to tackle streaming speaker change detection and gender classification by incorporating speaker embeddings into a transducer-based streaming end-to-end speech translation model.
Language Models as Continuous Self-Evolving Data Engineers
Large Language Models (LLMs) have demonstrated remarkable capabilities on various tasks, while the further evolvement is limited to the lack of high-quality training data.
Failing Forward: Improving Generative Error Correction for ASR with Synthetic Data and Retrieval Augmentation
To address these issues, we propose DARAG (Data- and Retrieval-Augmented Generative Error Correction), a novel approach designed to improve GEC for ASR in in-domain (ID) and OOD scenarios.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Improving Speech Recognition Error Prediction for Modern and Off-the-shelf Speech Recognizers
In this work, we extend a prior phonetic confusion based model for predicting speech recognition errors in two ways: first, we introduce a sampling-based paradigm that better simulates the behavior of a posterior-based acoustic model.
Soft Language Identification for Language-Agnostic Many-to-One End-to-End Speech Translation
Language-agnostic many-to-one end-to-end speech translation models can convert audio signals from different source languages into text in a target language.
Variational Optimization for Quantum Problems using Deep Generative Networks
Optimization is one of the keystones of modern science and engineering.
STICKERCONV: Generating Multimodal Empathetic Responses from Scratch
Stickers, while widely recognized for enhancing empathetic communication in online interactions, remain underexplored in current empathetic dialogue research, notably due to the challenge of a lack of comprehensive datasets.
Leveraging Timestamp Information for Serialized Joint Streaming Recognition and Translation
The growing need for instant spoken language transcription and translation is driven by increased global communication and cross-lingual interactions.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Improving Stability in Simultaneous Speech Translation: A Revision-Controllable Decoding Approach
Simultaneous Speech-to-Text translation serves a critical role in real-time crosslingual communication.
DiariST: Streaming Speech Translation with Speaker Diarization
End-to-end speech translation (ST) for conversation recordings involves several under-explored challenges such as speaker diarization (SD) without accurate word time stamps and handling of overlapping speech in a streaming fashion.
Token-Level Serialized Output Training for Joint Streaming ASR and ST Leveraging Textual Alignments
In real-world applications, users often require both translations and transcriptions of speech to enhance their comprehension, particularly in streaming scenarios where incremental generation is necessary.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Building High-accuracy Multilingual ASR with Gated Language Experts and Curriculum Training
We propose gated language experts and curriculum training to enhance multilingual transformer transducer models without requiring language identification (LID) input from users during inference.
Self-supervised learning with bi-label masked speech prediction for streaming multi-talker speech recognition
In this paper, we investigate SSL for streaming multi-talker speech recognition, which generates transcriptions of overlapping speakers in a streaming fashion.
LAMASSU: Streaming Language-Agnostic Multilingual Speech Recognition and Translation Using Neural Transducers
In this paper, we propose LAMASSU, a streaming language-agnostic multilingual speech recognition and translation model using neural transducers.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
A Weakly-Supervised Streaming Multilingual Speech Model with Truly Zero-Shot Capability
In this paper, we introduce our work of building a Streaming Multilingual Speech Model (SM2), which can transcribe or translate multiple spoken languages into texts of the target language.
Why does Self-Supervised Learning for Speech Recognition Benefit Speaker Recognition?
Recently, self-supervised learning (SSL) has demonstrated strong performance in speaker recognition, even if the pre-training objective is designed for speech recognition.
Large-Scale Streaming End-to-End Speech Translation with Neural Transducers
Neural transducers have been widely used in automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
A Conformer Based Acoustic Model for Robust Automatic Speech Recognition
The proposed model builds on the wide residual bi-directional long short-term memory network (WRBN) with utterance-wise dropout and iterative speaker adaptation, but employs a Conformer encoder instead of the recurrent network.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Predicting Atlantic Multidecadal Variability
Atlantic Multidecadal Variability (AMV) describes variations of North Atlantic sea surface temperature with a typical cycle of between 60 and 70 years.
Continuous Speech Separation with Recurrent Selective Attention Network
In this paper, we propose to apply recurrent selective attention network (RSAN) to CSS, which generates a variable number of output channels based on active speaker counting.
FloW: A Dataset and Benchmark for Floating Waste Detection in Inland Waters
To promote the practical application for autonomous floating wastes cleaning, we present FloW, the first dataset for floating waste detection in inland water areas.
Efficient End-to-End Speech Recognition Using Performers in Conformers
On-device end-to-end speech recognition poses a high requirement on model efficiency.
Multitask Training with Text Data for End-to-End Speech Recognition
We propose a multitask training method for attention-based end-to-end speech recognition models.
Speaker Separation Using Speaker Inventories and Estimated Speech
We propose speaker separation using speaker inventories and estimated speech (SSUSIES), a framework leveraging speaker profiles and estimated speech for speaker separation.
Multi-microphone Complex Spectral Mapping for Utterance-wise and Continuous Speech Separation
Although our system is trained on simulated room impulse responses (RIR) based on a fixed number of microphones arranged in a given geometry, it generalizes well to a real array with the same geometry.
Bridging the Gap Between Monaural Speech Enhancement and Recognition with Distortion-Independent Acoustic Modeling
In this study, we analyze the distortion problem, compare different acoustic models, and investigate a distortion-independent training scheme for monaural speech recognition.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Recurrent Deep Stacking Networks for Speech Recognition
This paper presented our work on applying Recurrent Deep Stacking Networks (RDSNs) to Robust Automatic Speech Recognition (ASR) tasks.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Incorporating Language Level Information into Acoustic Models
This paper proposed a class of novel Deep Recurrent Neural Networks which can incorporate language-level information into acoustic models.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
