Search Results for author:
Found 7 papers, 3 papers with code
RULER: What's the Real Context Size of Your Long-Context Language Models?
Despite achieving nearly perfect accuracy in the vanilla NIAH test, all models exhibit large performance drops as the context length increases.
Investigating End-to-End ASR Architectures for Long Form Audio Transcription
This paper presents an overview and evaluation of some of the end-to-end ASR models on long-form audios.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Fast Conformer with Linearly Scalable Attention for Efficient Speech Recognition
Conformer-based models have become the dominant end-to-end architecture for speech processing tasks.
Ranked #1 on
Speech Recognition
on LibriSpeech test-other
Accidental Learners: Spoken Language Identification in Multilingual Self-Supervised Models
In this paper, we extend previous self-supervised approaches for language identification by experimenting with Conformer based architecture in a multilingual pre-training paradigm.
Joint Detection and Coreference Resolution of Entities and Events with Document-level Context Aggregation
The tasks performed by this system are entity and event identification, typing, and coreference resolution.
QuartzNet: Deep Automatic Speech Recognition with 1D Time-Channel Separable Convolutions
We propose a new end-to-end neural acoustic model for automatic speech recognition.
Ranked #33 on
Speech Recognition
on LibriSpeech test-clean
Speech Recognition
Audio and Speech Processing
NeMo: a toolkit for building AI applications using Neural Modules
NeMo (Neural Modules) is a Python framework-agnostic toolkit for creating AI applications through re-usability, abstraction, and composition.
Ranked #1 on
Speech Recognition
on Common Voice Spanish
(using extra training data)
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
