9 citations · 10 across the 18 of their papers we have counts for
12 papers · 1 filter
From Speech to Interaction: Analyzing Multimodal Systems in Cocktail-Party Scenarios
Thai-Binh Nguyen, Zhaolin Li, Jan Niehues +1
Humans have the remarkable ability to engage in spontaneous informal conversations and selectively attend to individual speakers while filtering out competing speech from nearby co…
Adding Robust Code-Switching Capabilities to High Performance Multilingual ASR
Enes Yavuz Ugan, Alexander Waibel
Code-switching (CSW) remains challenging for large multi-lingual ASR systems in real-world deployment. While fine-tuning on synthetic CSW data is possible, it generally degrades st…
KIT's Submission to Cross-Lingual Voice Cloning in IWSLT 2026
Seymanur Akti, Alexander Waibel
Cross-lingual voice cloning aims to generate speech in a target language while preserving speaker identity from a source-language reference. This task is central to speech translat…
Adapting Language Balance in Code-Switching Speech
Enes Yavuz Ugan, Ngoc-Quan Pham, Alexander Waibel
Despite achieving impressive results on standard benchmarks, large foundational models still struggle against code-switching test cases. When data scarcity cannot be used as the us…
Bayesian Low-Rank Factorization for Robust Model Adaptation
Enes Yavuz Ugan, Ngoc-Quan Pham, Alexander Waibel
Large speech foundation models achieve strong performance across many domains, but they often require adaptation to handle local needs such as code-switching, where speakers mix la…
A Cocktail-Party Benchmark: Multi-Modal dataset and Comparative Evaluation Results
Thai-Binh Nguyen, Katerina Zmolikova, Pingchuan Ma +3
We introduce the task of Multi-Modal Context-Aware Recognition (MCoRec) in the ninth CHiME Challenge, which addresses the cocktail-party problem of overlapping conversations in a s…
Streaming Non-Autoregressive Model for Accent Conversion and Pronunciation Improvement
Tuan-Nam Nguyen, Ngoc-Quan Pham, Seymanur Akti +1
We propose a first streaming accent conversion (AC) model that transforms non-native speech into a native-like accent while preserving speaker identity, prosody and improving pronu…
Weight Factorization and Centralization for Continual Learning in Speech Recognition
Enes Yavuz Ugan, Ngoc-Quan Pham, Alexander Waibel
Modern neural network based speech recognition models are required to continually absorb new data without re-training the whole system, especially in downstream applications using…
KIT's Low-resource Speech Translation Systems for IWSLT2025: System Enhancement with Synthetic Data and Model Regularization
Zhaolin Li, Yining Liu, Danni Liu +6
This paper presents KIT's submissions to the IWSLT 2025 low-resource track. We develop both cascaded systems, consisting of Automatic Speech Recognition (ASR) and Machine Translati…
MSA-ASR: Efficient Multilingual Speaker Attribution with frozen ASR Models
Thai-Binh Nguyen, Alexander Waibel
Speaker-attributed automatic speech recognition (SA-ASR) aims to transcribe speech while assigning transcripts to the corresponding speakers accurately. Existing methods often rely…
Decoupled Vocabulary Learning Enables Zero-Shot Translation from Unseen Languages
Carlos Mullov, Ngoc-Quan Pham, Alexander Waibel
Multilingual neural machine translation systems learn to map sentences of different languages into a common representation space. Intuitively, with a growing number of seen languag…
Blending LLMs into Cascaded Speech Translation: KIT's Offline Speech Translation System for IWSLT 2024
Sai Koneru, Thai-Binh Nguyen, Ngoc-Quan Pham +4
Large Language Models (LLMs) are currently under exploration for various tasks, including Automatic Speech Recognition (ASR), Machine Translation (MT), and even End-to-End Speech T…