Analyzing Asr Pretraining For Low-Resource Speech-To-Text Translation


Previous research has demonstrated that pretraining an end-to-end model on automatic speech recognition (ASR) data from a high-resource language can improve automatic speech-to-text translation (AST) for low-resource source languages.

However, it is unclear which elements, such as language relatedness or the amount of the pretraining data, result in the greatest benefits, or whether pretraining can be effectively paired with other methods like data augmentation. We try out pretraining on a variety of datasets, including languages related and unrelated to the AST source language.

The word error rate of the pretrained ASR model is found to be the strongest predictor of final AST performance, and differences in ASR/AST performance correlate with how phonetic information is encoded in the subsequent RNN layers of our model. We also show that pretraining and data augmentation provide AST with additional benefits.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Adaptive Estimation of Time-Varying Sparse Signals ABSTRACT: We take a look at the challenge of designing adaptively compressive measurement matrices for the purpose of estimating time-varying sparse signals.
PROJECT TITLE :Sponsoring Mobile Data: Analyzing the Impact on Internet Stakeholders - 2018ABSTRACT:As demand for mobile information will increase, end users increasingly would like to pay additional for consuming data. Sponsored
PROJECT TITLE : Hierarchy-Cutting Model based Association Semantic for Analyzing Domain Topic on the Web - 2017 ABSTRACT: Association link network (ALN) can organize huge Web info to provide several intelligent services in
PROJECT TITLE : Analyzing Sentiments in One Go: A Supervised Joint Topic Modeling Approach - 2017 ABSTRACT: During this work, we focus on modeling user-generated review and overall rating pairs, and aim to spot semantic aspects
PROJECT TITLE :A New Measure for Analyzing and Fusing Sequences of ObjectsABSTRACT:This work is related to the combinatorial information analysis downside of seriation used for data visualization and exploratory analysis. Seriation

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry