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Found 7 papers, 2 papers with code
Hierarchical Recurrent Adapters for Efficient Multi-Task Adaptation of Large Speech Models
However, their per-task parameter overhead is considered still high when the number of downstream tasks to adapt for is large.
Streaming Parrotron for on-device speech-to-speech conversion
We present a streaming-based approach to produce an acceptable delay, with minimal loss in speech conversion quality, when compared to a reference state of the art non-streaming approach.
Non-Parallel Voice Conversion for ASR Augmentation
For ASR augmentation, it is necessary that the VC model be robust to a wide range of input speech.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
A Scalable Model Specialization Framework for Training and Inference using Submodels and its Application to Speech Model Personalization
We also show that learning a speaker-embedding space can scale further and reduce the amount of personalization training data required per speaker.
Real time spectrogram inversion on mobile phone
We present two methods of real time magnitude spectrogram inversion: streaming Griffin Lim(GL) and streaming MelGAN.
Residual Adapters for Parameter-Efficient ASR Adaptation to Atypical and Accented Speech
We demonstrate this on two speech adaptation tasks (atypical and accented speech) and for two state-of-the-art ASR architectures.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Direct speech-to-speech translation with a sequence-to-sequence model
We present an attention-based sequence-to-sequence neural network which can directly translate speech from one language into speech in another language, without relying on an intermediate text representation.
