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Anuj Diwan

7 accepted papers

2025

Dynamic-SUPERB Phase-2: A Collaboratively Expanding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 Tasks

ICLR 2025poster

Multimodal foundation models, such as Gemini and ChatGPT, have revolutionized human-machine interactions by seamlessly integrating various forms of data. Developing a universal spoken language model that comprehends a wide range of natural language instructions is critical for bridging communication…

2025

VoiceCraft-X: Unifying Multilingual, Voice-Cloning Speech Synthesis and Speech Editing

EMNLP 2025

We introduce VoiceCraft-X, an autoregressive neural codec language model which unifies multilingual speech editing and zero-shot text-to-speech (TTS) synthesis across 11 languages: English, Mandarin, Korean, Japanese, Spanish, French, German, Dutch, Italian, Portuguese, and Polish. VoiceCraft-X util

Cited by 0SourcePDFScholar
2024

Textless Speech-to-Speech Translation With Limited Parallel Data

EMNLP 2024finding

Existing speech-to-speech translation (S2ST) models fall into two camps: they either leverage text as an intermediate step or require hundreds of hours of parallel speech data. Both approaches are incompatible with textless languages or language pairs with limited parallel data. We present PFB, a fr…

2023

Continual Learning for On-Device Speech Recognition Using Disentangled Conformers

ICASSP 2023accepted

Automatic speech recognition research focuses on training and evaluating on static datasets. Yet, as speech models are increasingly deployed on personal devices, such models encounter user-specific distributional shifts. To simulate this real-world scenario, we introduce LibriContinual, a continual…

Cited by 0SourceScholar
2023

When to Use Efficient Self Attention? Profiling Text, Speech and Image Transformer Variants

ACL 2023short

We present the first unified study of the efficiency of self-attention-based Transformer variants spanning text, speech and vision. We identify input length thresholds (tipping points) at which efficient Transformer variants become more efficient than vanilla models, using a variety of efficiency me…

2022

Why is Winoground Hard? Investigating Failures in Visuolinguistic Compositionality

EMNLP 2022main

Recent visuolinguistic pre-trained models show promising progress on various end tasks such as image retrieval and video captioning. Yet, they fail miserably on the recently proposed Winoground dataset, which challenges models to match paired images and English captions, with items constructed to ov…