11 papers
TurboBias 2.0: Streaming Context-Biasing for Production-Efficient ASR Systems
Vladimir Bataev, Lilit Grigoryan, Andrei Andrusenko +3
Contextualization is essential for production automatic speech recognition (ASR) systems, where user-provided phrases must be recognized accurately under strict latency constraints…
Preference-ASR: A Preference-Aware Test Set for Benchmarking ASR in the Era of Speech LLMs
Nithin Rao Koluguri, Sasha Meister, Nikolay Karpov +4
Popular ASR test sets adopt inconsistent conventions for numbers, disfluencies, entities, and casing, while standard normalizers erase the format distinctions users care about. Cur…
Nemotron 3 Nano Omni: Efficient and Open Multimodal Intelligence
NVIDIA, :, Amala Sanjay Deshmukh +204
We introduce Nemotron 3 Nano Omni, the latest model in the Nemotron multimodal series and the first to natively support audio inputs alongside text, images, and video. Nemotron 3 N…
FlexCTC: GPU-powered CTC Beam Decoding With Advanced Contextual Abilities
Lilit Grigoryan, Vladimir Bataev, Nikolay Karpov +3
While beam search improves speech recognition quality over greedy decoding, standard implementations are slow, often sequential, and CPU-bound. To fully leverage modern hardware ca…
Open Automatic Speech Recognition Models for Classical and Modern Standard Arabic
Lilit Grigoryan, Nikolay Karpov, Enas Albasiri +2
Despite Arabic being one of the most widely spoken languages, the development of Arabic Automatic Speech Recognition (ASR) systems faces significant challenges due to the language'…
Unified Semi-Supervised Pipeline for Automatic Speech Recognition
Nune Tadevosyan, Nikolay Karpov, Andrei Andrusenko +2
Automatic Speech Recognition has been a longstanding research area, with substantial efforts dedicated to integrating semi-supervised learning due to the scarcity of labeled datase…
Granary: Speech Recognition and Translation Dataset in 25 European Languages
Nithin Rao Koluguri, Monica Sekoyan, George Zelenfroynd +12
Multi-task and multilingual approaches benefit large models, yet speech processing for low-resource languages remains underexplored due to data scarcity. To address this, we presen…
Methods to Increase the Amount of Data for Speech Recognition for Low Resource Languages
Alexan Ayrapetyan, Sofia Kostandian, Ara Yeroyan +5
This study explores methods to increase data volume for low-resource languages using techniques such as crowdsourcing, pseudo-labeling, advanced data preprocessing and various perm…
Enabling ASR for Low-Resource Languages: A Comprehensive Dataset Creation Approach
Ara Yeroyan, Nikolay Karpov
In recent years, automatic speech recognition (ASR) systems have significantly improved, especially in languages with a vast amount of transcribed speech data. However, ASR systems…
The CHiME-7 Challenge: System Description and Performance of NeMo Team's DASR System
Tae Jin Park, He Huang, Ante Jukic +7
We present the NVIDIA NeMo team's multi-channel speech recognition system for the 7th CHiME Challenge Distant Automatic Speech Recognition (DASR) Task, focusing on the development…
LibriSpeech-PC: Benchmark for Evaluation of Punctuation and Capitalization Capabilities of end-to-end ASR Models
Aleksandr Meister, Matvei Novikov, Nikolay Karpov +3
Traditional automatic speech recognition (ASR) models output lower-cased words without punctuation marks, which reduces readability and necessitates a subsequent text processing mo…