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Found 10 papers, 2 papers with code
Self-Supervised Representations for Singing Voice Conversion
A singing voice conversion model converts a song in the voice of an arbitrary source singer to the voice of a target singer.
Synthetic Cross-accent Data Augmentation for Automatic Speech Recognition
In this work, we improve an accent-conversion model (ACM) which transforms native US-English speech into accented pronunciation.
Biased Self-supervised learning for ASR
Furthermore, this paper proposes a variant of MPPT that allows low-footprint streaming models to be trained effectively by computing the MPPT loss on masked and unmasked frames.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Towards Measuring Fairness in Speech Recognition: Casual Conversations Dataset Transcriptions
This paper presents initial Speech Recognition results on "Casual Conversations" -- a publicly released 846 hour corpus designed to help researchers evaluate their computer vision and audio models for accuracy across a diverse set of metadata, including age, gender, and skin tone.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Ego4D: Around the World in 3,000 Hours of Egocentric Video
We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite.
Worldly Wise (WoW) - Cross-Lingual Knowledge Fusion for Fact-based Visual Spoken-Question Answering
Three sub-tasks are proposed: (1) speech-to-text based, (2) end-to-end, without speech-to-text as an intermediate component, and (3) cross-lingual, in which the question is spoken in a language different from that in which the KG is recorded.
A Multi-View Approach To Audio-Visual Speaker Verification
Although speaker verification has conventionally been an audio-only task, some practical applications provide both audio and visual streams of input.
Deep F-measure Maximization for End-to-End Speech Understanding
We propose a differentiable approximation to the F-measure and train the network with this objective using standard backpropagation.
Identify Speakers in Cocktail Parties with End-to-End Attention
In scenarios where multiple speakers talk at the same time, it is important to be able to identify the talkers accurately.
Unsupervised Speaker Adaptation using Attention-based Speaker Memory for End-to-End ASR
We propose an unsupervised speaker adaptation method inspired by the neural Turing machine for end-to-end (E2E) automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
