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Found 6 papers, 2 papers with code
Language ID Prediction from Speech Using Self-Attentive Pooling
This memo describes NTR-TSU submission for SIGTYP 2021 Shared Task on predicting language IDs from speech.
Using a Language Model in a Kiosk Recommender System at Fast-Food Restaurants
Kiosks are a popular self-service option in many fast-food restaurants, they save time for the visitors and save labor for the fast-food chains.
Low-Resource Spoken Language Identification Using Self-Attentive Pooling and Deep 1D Time-Channel Separable Convolutions
In this memo, we show that a convolutional neural network with a Self-Attentive Pooling layer shows promising results in low-resource setting for the language identification task and set up a SOTA for the Low Resource ASR challenge dataset.
Language ID Prediction from Speech Using Self-Attentive Pooling and 1D-Convolutions
This memo describes NTR-TSU submission for SIGTYP 2021 Shared Task on predicting language IDs from speech.
MediaSpeech: Multilanguage ASR Benchmark and Dataset
The performance of automated speech recognition (ASR) systems is well known to differ for varied application domains.
Ranked #1 on
Speech Recognition
on MediaSpeech
Learning Efficient Representations for Keyword Spotting with Triplet Loss
In the past few years, triplet loss-based metric embeddings have become a de-facto standard for several important computer vision problems, most no-tably, person reidentification.
Ranked #1 on
Keyword Spotting
on Google Speech Commands
