Robust Speech Recognition Using Generative Adversarial Networks

This paper describes a general, scalable, end-to-end framework that uses the generative adversarial network (GAN) objective to enable robust speech recognition. Encoders trained with the proposed approach enjoy improved invariance by learning to map noisy audio to the same embedding space as that of clean audio. Unlike previous methods, the new framework does not rely on domain expertise or simplifying assumptions as are often needed in signal processing, and directly encourages robustness in a data-driven way. We show the new approach improves simulated far-field speech recognition of vanilla sequence-to-sequence models without specialized front-ends or preprocessing

Cold Fusion: Training Seq2Seq Models Together with Language Models

Sequence-to-sequence (Seq2Seq) models with attention have excelled at tasks which involve generating natural language sentences such as machine translation, image captioning and speech recognition. Performance has further been improved by leveraging unlabeled data, often in the form of a language model. In this work, we present the Cold Fusion method, which leverages a pre-trained language model during training, and show its effectiveness on the speech recognition task. We show that Seq2Seq models with Cold Fusion are able to better utilize language information enjoying i) faster convergence and better generalization, and ii) almost complete transfer to a new domain while using less than 10% of the labeled training data

Identification of a quadruple mutation that confers tenofovir resistance in chronic hepatitis B patients

International audienceBackground & aims: Tenofovir disoproxil fumarate (TDF) is one the most potent nucleot(s)ide analogues for treating chronic hepatitis B virus (HBV) infection. Phenotypic resistance caused by genotypic resistance to TDF has not been reported. This study aimed to characterize HBV mutations that confer tenofovir resistance.Methods: Two patients with viral breakthrough during treatment with TDF-containing regimens were prospectively enrolled. The gene encoding HBV reverse transcriptase was sequenced. Eleven HBV clones harboring a series of mutations in the reverse transcriptase gene were constructed by site-directed mutagenesis. Drug susceptibility of each clone was determined by Southern blot analysis and real-time PCR. The relative frequency of mutants was evaluated by ultra-deep sequencing and clonal analysis.Results: Five mutations (rtS106C [C], rtH126Y [Y], rtD134E [E], rtM204I/V, and rtL269I [I]) were commonly found in viral isolates from 2 patients. The novel mutations C, Y, and E were associated with drug resistance. In assays for drug susceptibility, the IC50 value for wild-type HBV was 3.8 ± 0.6 µM, whereas the IC50 values for CYE and CYEI mutants were 14.1 ± 1.8 and 58.1 ± 0.9 µM, respectively. The IC90 value for wild-type HBV was 30 ± 0.5 µM, whereas the IC90 values for CYE and CYEI mutants were 185 ± 0.5 and 790 ± 0.2 µM, respectively. Both tenofovir-resistant mutants and wild-type HBV had similar susceptibility to the capsid assembly modulator NVR 3-778 (IC50 10-fold resistance to tenofovir up to 8 years. Herein, we identified, for the first time, a quadruple mutation that conferred 15.3-fold (IC50) and 26.3-fold (IC90) resistance to tenofovir in 2 patients who experienced viral breakthrough during tenofovir treatment