ASR AUTOMATIC SPEECH RECOGNITION 2019


Speech recognition software works by breaking down the audio of a speech recording into individual sounds, analyzing each sound, using algorithms to find the most probable word fit in that language, and transcribing those sounds into text.

algorithms used in this form of technology include PLP features, Viterbi search, deep neural networks, discrimination training, WFST framework

Improving asr systems for children with autism and language impairment using domain-focused dnn transfer techniques
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This study explores building and improving an automatic speech recognition ( ASR ) system for children aged 6-9 years and diagnosed with autism spectrum disorder (ASD), language impairment (LI), or both. Working with only 1.5 hours of target data in which children perform

The JHU ASR System for VOiCES from a Distance Challenge 2019
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This paper describes the system developed by the JHU team for automatic speech recognition ( ASR ) of the VOiCES from a Distance Challenge 201 focusing on single channel distant/farfield audio under noisy conditions. We participated in the Fixed Condition

Joint Grapheme and Phoneme Embeddings for Contextual End-to-End ASR
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End-to-end approaches to automatic speech recognition, such as Listen-Attend-Spell (LAS), blend all components of a traditional speech recognizer into a unified model. Although this simplifies training and decoding pipelines, a unified model is hard to adapt when mismatch

Mechanistic Role of Supplementary Cementitious Materials (SCMs) in Alkali-Silica Reaction ( ASR ) Mitigation
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Alkali-silica reaction ( ASR ) can cause premature failure of concrete structures and therefore is a major concrete durability issue. The use of commonly available supplementary cementitious materials (SCMs) such as fly ash and slag is generally regarded as the most

Deep Learning based Mandarin Accent Identification for Accent Robust ASR
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In this paper, we present an in-depth study on the classification of regional accents in Mandarin speech. Experiments are carried out on Mandarin speech data systematically collected from 15 different geographical regions in China for broad coverage. We explore

Predicting Speech Intelligibility of Enhanced Speech Using Phone Accuracy of DNN-based ASR System
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The ability of state-of-the-art automatic speech recognition ( ASR ) systems, which use deep neural networks (DNN), has recently been approaching that of human auditory systems. On the other hand, although measuring the intelligibility of enhanced speech signals is

Impact of ASR Performance on Spoken Grammatical Error Detection
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Computer assisted language learning (CALL) systems aid learners to monitor their progress by providing scoring and feedback on language assessment tasks. Free speaking tests allow assessment of what a learner has said, as well as how they said it. For these tasks

A regularized damage model for structural analyses of concrete dams in the presence of ASR .
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Concrete is one of the most used materials in civil engineering, but its durability can be reduced by several chemical phenomena, among them the alkali-silica reaction ( ASR ) plays a fundamental role. During ASR amorphous silica of aggregates reacts with the high

A comparison of transformer and lstm encoder decoder models for asr
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We present competitive results using a Transformer encoderdecoder-attention model for end- to-end speech recognition needing less training time compared to a similarly performing LSTM model. We observe that the Transformer training is in general more stable compared

Performance Comparison of Deep Neural Network Quantizers to Continuous ASR Systems
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Continuous approaches where a Hidden Markov Model (HMM) is combined with a Gaussian Mixture Model (GMM)/Deep Neural Network (DNN) are still one of the most popular architectures in Automatic Speech Recognition ( ASR ). They performed well on several

Modulation Vectors as Robust Feature Representation for ASR in Domain Mismatched Conditions}}
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In this work, we demonstrate the robustness of Modulation Vectors, in domain mismatches between the training and test conditions in an Automatic Speech Recognition ( ASR ) system. Our work focuses on the specific task of dealing with mismatches caused by reverberation

Reliability of extending AS1141. 60.1 and 60.2 test methods to determine ASR mitigation
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Abstract The Australian Standards AS 1141.60. 1 and AS 1141.60. 2 were published in 2014 as Accelerated Mortar Bar Test (AMBT) and Concrete Prism Test (CPT) to determine the potential alkali-silica reactivity ( ASR ) of aggregates. Both methods were extended to

Improving ASR confidence scores for Alexa using acoustic and hypothesis embeddings
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In automatic speech recognition, confidence measures provide a quantitative representation used to assess whether a generated hypothesis text is correct or not. For personal assistant devices like Alexa, automatic speech recognition ( ASR ) errors are inevitable due to the With regards to European waste catalog, automotive shredder residues ( ASR ) can be classified both as a hazardous or non-hazardous waste according to its hazardous properties (H1 H14). It is thus important to carry out an adequate chemical-physical

Mechanical properties of ASR affected concrete: a critical review
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Alkali-silica reaction ( ASR ) in concrete can induce degradation to its mechanical properties, leading to compromised serviceability and even loss in load carrying capacity of concrete structures. Considering the importance of the problem, extensive studies mostly by means of

The I2Rs ASR System for the VOiCES from a Distance Challenge 2019
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This paper describes the development of the automatic speech recognition ( ASR ) system for the submission to the VOiCES from a Distance Challenge 2019. In this challenge, we focused on the fixed condition, where the task is to recognize reverberant and noisy speech Shredder is the equipment used for ferrous scrap grinding that enables the recycling of steel in steel mills. The scrap is mostly originated from end-of-life vehicles (ELV). Therefore, this residue is known as automotive shredder residue ( ASR ). Throughout the world, is estimated

Say what A dataset for exploring the error patterns that two ASR engines make
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We present a new metadataset which provides insight into where and how two ASR systems make errors on several different speech datasets. By making this data readily available to researchers, we hope to stimulate research in the area of WER estimation models, in order

FINITE ELEMENT ANALYSIS OF WALLS WITH ALKALI-SILICA REACTION ( ASR ) SUBJECTED TO CONSTANT AXIAL AND CYCLIC LATERAL LOADINGS
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ABSTRACT Alkali Silica Reaction ( ASR ), a type of alkali aggregate Reaction (AAR), is observed in some concrete structures in eastern Canada and the eastern United States. The Canadian Nuclear Safety Commission (CNSC) is currently conducting research to develop

ASR -Related Distress in Floor Coatings
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Alkali-silica reaction ( ASR ) is a common distress mechanism associated with certain aggregates in portland cement concrete. 1 ASR occurs when glassy, cryptocrystalline, microcrystalline, or physically strained silica (all chemically SiO2) reacts with the alkaline


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