Speech Recognition 2021




Using Radio Archives for Low-Resource Speech Recognition : Towards an Intelligent Virtual Assistant for Illiterate Users
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For many of the 700 million illiterate people around the world, speech recognition technology could provide a bridge to valuable information and services. Yet, those most in need of this technology are often the most underserved by it. In many countries, illiterate This paper demonstrates the effect of incorporating Deep Neural Network techniques in speech recognition systems. Speech recognition through hybrid Deep Neural Networks on the Kaldi toolkit for the Punjabi language is implemented. Performance of the automaticPurpose To investigate the impact of the amount of depressive symptoms in cochlear implant (CI) recipients on the development of speech recognition after CI-activation up to 2 years. Design Retrospective data analysis of a German short form of the Beck Depression

Malayalam Speech Recognition
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The project is based on the development of state-of-the-art large vocabulary continuous speech recognition (LVCSR) system for the Malayalam language. Problems of existing speech recognition are lack of accuracy and misinterpretation, time cost and productivity

A Brief Analysis of the Dual Influences of Speech Recognition Assistance on Simultaneous Interpretation
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In the era of artificial intelligence, big data, speech recognition machine translation and other technologies have brought an increasing impact on the field of manual translation. On the one hand, it challenges manual translation, and on the other hand, it assists andThe process of speech recognition is such that a speech signal from a client or user is received by the system through a microphone, then the system analyses this signal and extracts useful information from the signal which is converted to text. This study focuses on

Classification approaches for automatic speech recognition system
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Recognition of Speech is now becoming more widespread. Different applications that are knowledgeable of interactive expression are present on the market. For those devices in which handwriting is complicated, speaking recognition systems are sensible options. With

Multilingual Sequence-To-Sequence Speech Recognition
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There are a multitude of languages and dialects in the world. To develop a speech recognition system for all of them is an expensive and time-consuming task. Multilingual systems can be advantageous here, but dont work as good as monolingual ones currently

Speech Recognition
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Speech is a simple and effort less approach of communication amongst humans, but in this day and age humans are not restricted to connecting to one another but even to the various machines in their lives. The most essential being the computer. So, this communication

Assessing the Practicality of Using an Automatic Speech Recognition Tool to Teach English Pronunciation Online
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This study aims to determine how well an automatic speech recognition (ASR) tool could be used in an online EFL course to help L1 Japanese students improve their pronunciation. Previous studies have suggested that ASR tools can be helpful in this regard, but few have

Myan Continuous Speech Recognition System Using Convolutional Neural Network
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Translating the human speech signal into the text words is also known as Automatic Speech Recognition System (ASR) that is still many challenges in the processes of continuous speech recognition . Recognition System for Continuous speech develops with the fourThe paper presents experiments on the use of automatic speech recognition for diagnostic evaluation of synthetic speech. Our previous work on the topic showed a strong correlation between the subjective and objective evaluation (ITU-T Rec. P. 862 PESQ) of the quality of

The convolutional neural networks for Amazigh speech recognition system
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In this paper, we present an approach based on convolutional neural networks to build an automatic speech recognition system for the Amazigh language. This system is built with TensorFlow and uses mel frequency cepstral coefficient (MFCC) to extract features. In order

A STUDY ON SPEECH RECOGNITION
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The primary mode of communication is language, and speech is its primary medium. Speech is the most fundamental form of human communication. Speech recognition is a way of converting speech sounds into text. Nonetheless, there are many important research

Speech Recognition Technology for OPAC Service: An Innovative Idea for Indian Libraries
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The Information and Communication Technology (ICT) driven environment compelled to software engineers and professionals to work harder to meet out the expectations of the people needs and requirements. The smartphone savvy generation is more acquainted with

Concatenative Speech Recognition using Morphemes
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This paper adopts a novel sub-lexical approach to construct viable continuous speech recognition systems with scalable vocabulary that use the components of words to form the elements of pronunciation dictionaries and recognition lattices. The proposed Concatenative

HMM-based phoneme speech recognition system for the control and command of industrial robots. Technical
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In recent years, the integration of human-robot interaction with speech recognition has gained a lot of pace in the manufacturing industries. Conventional methods to control the robots include semi-autonomous, fully-autonomous, and wired methods. Operating through

Evaluating the Vulnerability of End-to-End Automatic Speech Recognition Models To Membership Inference Attacks
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Recent studies have shown that it be possible to determine if a machine learning model was trained on a given data sample, using Membership Inference Attacks (MIA). In this paper we evaluate the vulnerability of state-of-the-art speech recognition models to MIA

Speech Recognition using Deep Canonical Correlation Analysis in Noisy Environments.
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In this paper, we propose a method to improve the accuracy of speech recognition in noisy environments by utilizing Deep Canonical Correlation Analysis (DCCA). DCCA generates projections from two modalities into one common space, so that the correlation of projected

Speech recognition (Respeaking) vs. the conventional method (Keyboard): A quality-oriented comparison of speech-to-text interpreting techniques and
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Speech-to-text interpreting (STTI) is especially in the German-speaking area still a young profession, but it is used more and more, not least thanks to the UN Convention on the Rights of Persons with Disabilities and the national legislations that derive from it. Over time

Automatic Speech Recognition systems errors for accident-prone sleepiness detection through voice
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Excessive Daytime Sleepiness (EDS), a symptom linked to chronic sleepiness, impacts everyday life and increases risks of work or road accidents of subjects affected by it. The detection of accident-prone EDS through voice benefits from its ease to be implemented in

A SURVEY PAPER ON SPEECH RECOGNITION SYSTEM
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By composing in the inquiry choice bar, it helps in looking through the applications in windows 7. There is no such application inherent windows that can serve to convert discourse into text. Discourse acknowledgment is a mind boggling order undertaking and

Is Speech Recognition Software a Viable Future for Dysarthric Speakers A Critical Review
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The idea of speech recognition software, in its purest form opens the possibilities for individuals with dysarthria to bypass one of their biggest barriers, being difficulties with speech clarity. This critical review explored the relationship between speech to text software

Filter Bank Effects on Detecting Adversarial Speech Recognition Attacks In Noise
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In an existence of ever more internet connected devices and increasing number of input modalities, systems employing visionary and auditory modes of interaction with the world, become ever so slightly more exposed to adversarial behaviour. A very recent vision

Integration of Audio video Speech Recognition using LSTM and Feed Forward Convolutional Neural Network
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In the current scenario, audio visual speech recognition is one of the emerging fields of research, but there is still deficiency of appropriate visual features for recognition of visual speech. Human lip-readers are increasingly being presented as useful in the gathering ofIn this work we perform automatic recognition of continuous speech signal spoken in Gujarati language using machine learning (ML) technique. For this purpose, from continuous speech signal of sentence we first extract words using short term auto-correlation

Speak2Code: A Multi-Utility Program based on Speech Recognition that Allows you to Code Through Speech Commands
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Voice recognition has gained prominence and extensive use with the rise of Artificial Intelligence and that of the intelligent assistants such as Amazons Alexa, Apples Siri and Microsofts Cortana. Voice recognition systems enable Coders to interact with IDEs, Coding

Deep Scattering and End-to-End Speech Models towards Low Resource Speech Recognition
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Automatic Speech Recognition (ASR) has made major leaps in its advancement largely due to two different machine learning models: Hidden Markov Models (HMMs) and Deep Neural Networks (DNNs). State-of-the art results have been achieved by combining these two

EMOTION BIAS IN AUTOMATIC SPEECH RECOGNITION
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In this paper, we investigate the effect of emotions on an established automatic speech recognition system using five emotional speech databases covering English, German, and Italian language. We computed the word error rates and the significance of the ratio between

Augmenting Harper Valley Bank: Robust Automatic Speech Recognition
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Abstract The newly introduced Harper Valley Bank Dataset serves as a testbed for techniques in the field of spoken language processing. In this paper, we tackle LASs tendency to overfit on the HVB dataset by using a combination of augmentation techniques

Improved text normalization and language models for SpeeDs Automatic Speech Recognition System
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Automatic speech recognition (ASR) systems that use word-based language models require periodical updates to include new named entities (eg. coronavirus, COVID-19) or collocations. Moreover, in particular for the Romanian language, the new hyphenated words

REVIEW ON SMALL VOCABULARY AUTOMATIC SPEECH RECOGNITION SYSTEM (ASR) FOR MARATHI
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Speech interfaces make available people an easy and comfortable means to interact with human and Laptop Systems or PC. This paper is an attempt to study the Small Vocabulary Speech Recognition System for Marathi Using Automatic Speech Recognition System

Automatic Speech Recognition in the French
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For millennia, speech has been the most natural communication tool for humans. As a result, with the emergence of computer science and signal processing, tremendous efforts have been made in the field of Automatic Speech Recognition (ASR). In fact, it has been an active

TOWARDS RELIABILITY-GUIDED INFORMATION INTEGRATION IN AUDIO-VISUAL SPEECH RECOGNITION
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Audio-visual speech recognition can improve the recognition rate in many small-vocabulary tasks. But for large vocabularies, due to difficulties like unsatisfactory lipreading accuracies, improving the recognition rate over audioonly baselines remains difficult. In this work, we

Using a logical Derivative to Determine the Information Content of Object Properties in Speech Recognition Tasks
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This paper offers an approach for determining the information content of object properties in recognition tasks. The scope of this approach is not the subject area where objects and characteristics of these objects are specified, but a trained ΣΠ-neural network that works

TRIBUS: An end-to-end automatic speech recognition system for European Portuguese
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End-to-end automatic speech recognition (ASR) approaches have emerged as a competitive alternative to traditional HMM-based ASR systems. Unfortunately, most end-to- end ASR systems are not easily reproduced since they require vast amounts of data and

Investigating the scarce data and resources problem for speech recognition using transfer learning and data augmentation
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We investigate the effect of the transfer learning procedure on e2e Automatic Speech Recognition systems using a limited amount of data. We use a DeepSpeech inspired base- line in our experiments and based on different transfer learning techniques. Our

Indigenuous Vocabulary Reformulation for Continuousyorùbá Speech Recognition In M-Commerce Using Acoustic Nudging-Based Gaussian Mixture Model
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One of the current research areas is speech recognition by aiding in the recognition of speech signals through computer applications. In this research paper, Acoustic Nudging,(AN) Model is used in re-formulating the persistence automatic speech recognition

GMM and LDA based Speech recognition using Sonogram
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Automatic recognition of speech using computers is a challenging issue. This paper describes a techniques that uses Gaussian mixture model (GMM) and Linear Discriminate Analysis (LDA) to recognized speech based on features using Sonogram. Modeling

AUTOMATIC-SUBTITLING: COMPARISON ON THE PERFORMANCE OF FORCED ALIGNMENT AND AUTOMATIC SPEECH RECOGNITION
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This work is focusing on the automatic generation of subtitles using different tools that can be categorized as Forced Aligners (FAs) or Automatic Speech Recognizers (ASRs). A comparison of the performance of FA and ASR for the task of generating same-language