Of round 7,000 languages on the planet, a tiny fraction are supported by AI language fashions. NVIDIA is tackling the issue with a brand new dataset and fashions that help the event of high-quality speech recognition and translation AI for 25 European languages — together with languages with restricted out there information like Croatian, Estonian and Maltese.
These instruments will allow builders to extra simply scale AI purposes to help world customers with quick, correct speech expertise for production-scale use circumstances akin to multilingual chatbots, customer support voice brokers and near-real-time translation companies. They embody:
- Granary, a large, open-source corpus of multilingual speech datasets that accommodates round one million hours of audio, together with practically 650,000 hours for speech recognition and over 350,000 hours for speech translation.
- NVIDIA Canary-1b-v2, a billion-parameter mannequin skilled on Granary for high-quality transcription of European languages, plus translation between English and two dozen supported languages.
- NVIDIA Parakeet-tdt-0.6b-v3, a streamlined, 600-million-parameter mannequin designed for real-time or large-volume transcription of Granary’s supported languages.
The paper behind Granary might be offered at Interspeech, a language processing convention happening within the Netherlands, Aug. 17-21. The dataset, in addition to the brand new Canary and Parakeet fashions, at the moment are out there on Hugging Face.
How Granary Addresses Knowledge Shortage
To develop the Granary dataset, the NVIDIA speech AI workforce collaborated with researchers from Carnegie Mellon College and Fondazione Bruno Kessler. The workforce handed unlabeled audio by an revolutionary processing pipeline powered by NVIDIA NeMo Speech Knowledge Processor toolkit that turned it into structured, high-quality information.
This pipeline allowed the researchers to reinforce public speech information right into a usable format for AI coaching, with out the necessity for resource-intensive human annotation. It’s out there in open supply on GitHub.
With Granary’s clear, ready-to-use information, builders can get a head begin constructing fashions that deal with transcription and translation duties in practically all the European Union’s 24 official languages, plus Russian and Ukrainian.
For European languages underrepresented in human-annotated datasets, Granary offers a vital useful resource to develop extra inclusive speech applied sciences that higher replicate the linguistic variety of the continent — all whereas utilizing much less coaching information.
The workforce demonstrated of their Interspeech paper that, in comparison with different fashionable datasets, it takes round half as a lot Granary coaching information to attain a goal accuracy stage for computerized speech recognition (ASR) and computerized speech translation (AST).
Tapping NVIDIA NeMo to Turbocharge Transcription
The brand new Canary and Parakeet fashions supply examples of the sorts of fashions builders can construct with Granary, personalized to their goal purposes. Canary-1b-v2 is optimized for accuracy on complicated duties, whereas parakeet-tdt-0.6b-v3 is designed for high-speed, low-latency duties.
By sharing the methodology behind the Granary dataset and these two fashions, NVIDIA is enabling the worldwide speech AI developer group to adapt this information processing workflow to different ASR or AST fashions or further languages, accelerating speech AI innovation.
Canary-1b-v2, out there underneath a permissive license, expands the Canary household’s supported languages from 4 to 25. It affords transcription and translation high quality similar to fashions 3x bigger whereas working inference as much as 10x sooner.
NVIDIA NeMo, a modular software program suite for managing the AI agent lifecycle, accelerated speech AI mannequin improvement. NeMo Curator, a part of the software program suite, enabled the workforce to filter out artificial examples from the supply information in order that solely high-quality samples had been used for mannequin coaching. The workforce additionally harnessed the NeMo Speech Knowledge Processor toolkit for duties like aligning transcripts with audio information and changing information into the required codecs.
Parakeet-tdt-0.6b-v3 prioritizes excessive throughput and is able to transcribing 24-minute audio segments in a single inference move. The mannequin routinely detects the enter audio language and transcribes with out further prompting steps.
Each Canary and Parakeet fashions present correct punctuation, capitalization and word-level timestamps of their outputs.
Learn extra on GitHub and get began with Granary on Hugging Face.