Автоматты сөйлеуді тану

In natural speech, durations of phonetic segments are strongly de- pendent on contextual factors. Quantitative descriptions of these contextual effects have appfications in text-to-speech synthesis and in automatic speech recognition. …...

Much interest already exists in the electronics research community for developing and integrating speech technology to a variety of ap- plications, ranging from voice-activated systems to automatic tele- phone transactions. …...

AbstractWeighted automata and transducers are used in a variety of applications ranging from automatic speech recognition and synthesis to computational biology. They give a unifying framework for the representation of …...

This paper describes SCANMail, a system that allows users to browse and search their voicemail messages by content through a GUI. Content based navigation is realized by use of automatic …...

Traditional approaches to Information Ex- traction (IE) from speech input simply consist in applying text based methods to the output of an Automatic Speech Recog- nition (ASR) system. If it …...

Browsing through large volumes of spoken audio is known to be a challenging task for end users. One way to alleviate this prob- lem is to allow users to gist …...

AbstractIn TC-STAR a variety of Language Resources (LR) is being produced. In this contribution we address the resources that have been created for Automatic Speech Recrognition and Spoken Language Translation. …...

Over the past decade, computational linguists have been striving to design a speech recognition system that is able to identify standard speeches and to accommodate sound variables caused by different …...

. This work is part of a large research project entitled "Oreillodule" aimed at developing tools for automatic speech recognition, translation, and synthesis for Arabic language. Our attention has mainly …...

Electronic written texts used in computer- mediated interactions (e-mails, blogs, chats, etc) present major deviations from the norm of the language. This paper presents an comparative study of systems aiming …...

Mobile voice-enabled search is emerging as one of the most popular applications abetted by the exponential growth in the number of mobile devices. The automatic speech recognition (ASR) output of …...

AbstractTypical broadcast material contains not only studio-recorded texts read by trained speakers, but also spontaneous and dialect speech, debates with cross-talk, voice-overs, and on-site reports with difficult acoustic environments. Standard …...

AbstractRepetition is a common concept in human communication. This paper investigates possible benefits of repetition for automatic speech recognition under controlled conditions. Testing is performed on the newly created Autonomata …...

There is considerable interest in interdis- ciplinary combinations of automatic speech recognition (ASR), machine learning, natu- ral language processing, text classification and information retrieval. Many of these boxes, especially ASR, …...

. In this invited paper, we introduce a public web service, PodCastle, that pro- vides full-text searching of speech data (Japanese podcasts) on the basis of automatic speech recognition technologies. …...

AbstractThis paper describes the Alborada-I3A corpus of disordered speech, acquired during the recent years for the research in different speech technologies for the handicapped like Automatic Speech Recognition or pronunciation …...

AbstractThe SignSpeak project will be the first step to approach sign language recognition and translation at a scientific level already reached in similar research fields such as automatic speech recognition …...

AbstractIt is well-known that human listeners significantly outperform machines when it comes to transcribing speech. This paper presents a progress report of the joint research in the automatic vs human …...

Developments of Swahili resources for an automatic speech recognition system This article describes our efforts to provide ASR resources for Swahili, a Bantu language spoken in a wide area of …...

Assessment of the acoustic models performance in the ageing voice case for ASR system adaptation Our study concerns the integration of an automatic speech recognition system in a social inclusion …...

LDA-based tagging of Web videos This article presents a method for the automatic tagging of youtube videos. The proposed me- thod combines an automatic speech recognition system, that extracts the …...

Impact of the level of supervision on Web-based language model domain adaptation Domain adaptation of a language model aims at re-estimating word sequence probabilities in order to better match the …...

Percol0 - A multimodal person detection system in video documents The goal of the PERCOL project is to participate to the REPERE multimodal evaluation program by building a consortium combining …...

Prediction of transcription indexability This paper presents a semantic confidence measure that aims to predict the relevance of automatic transcripts for a task of Spoken Document Retrieval (SDR). The proposed …...

This paper develops a new statistical method of building language models (LMs) of Japanese dialects for automatic speech recognition (ASR). One possible application is to recognize a variety of utterances …...

AbstractLuxembourgish, embedded in a multilingual context on the divide between Romance and Germanic cultures, remains one of Europe’s under-described languages. This is due to the fact that the written production …...

We address the problem of estimating the quality of Automatic Speech Recognition (ASR) out- put at utterance level, without recourse to manual reference transcriptions and when information about system’s confidence …...

We present a novel way of generating un- seen words, which is useful for certain ap- plications such as automatic speech recog- nition or optical character recognition in low-resource languages. …...

We investigate the problem of predicting the quality of automatic speech recognition (ASR) output under the following rigid con- straints: i) reference transcriptions are not available, ii) confidence information about …...

Automatic analysis of impaired speech for screening or diagnosis is a growing research field; however there are still many barriers to a fully automated approach. When automatic speech recognition is …...

AbstractSpeech that contains multimedia content can pose a serious challenge for real-time automatic speech recognition (ASR) for two reasons: (1) The ASR produces meaningless output, hurting the readability of the …...

AbstractIn order to apply computational linguistic analyses and pass information to downstream applications, transcriptions of speech obtained via automatic speech recognition (ASR) need to be divided into smaller meaningful units, …...

AbstractThe paper steps outside the comfort-zone of the traditional NLP tasks like automatic speech recognition (ASR) and machine translation (MT) to addresses two novel problems arising in the automated multilingual …...

AbstractThis project approaches the problem of language documentation and revitalization from a rather untraditional angle. To improve and facilitate language documentation of endangered languages, we attempt to use corpus linguistic …...

AbstractIn sources used in oral history research (such as interviews with eye witnesses), passages where the degree of personal emotional involvement is found to be high can be of particular …...

The main aim of this paper is to investigate automatic quality assessment for spoken language translation (SLT). More precisely, we investigate SLT errors that can be due to transcription (ASR) …...

AbstractEnd-to-end automatic speech recognition (ASR) has become a popular alternative to conventional DNN/HMM systems because it avoids the need for linguistic resources such as pronunciation dictionary, tokenization, and context-dependency trees, …...

Despite its potential utility for facilitating the transcription of speech recordings, automatic speech recognition (ASR) has not been widely explored as a tool for documenting endangered languages. One obstacle to …...

Automatic speech recognition is a requested technique in many fields like automatic subtitling, dialogue systems and information retrieval systems. The training of an automatic speech recognition system is usually straight …...

This paper describes different approaches to improve the transcription and indexing quality of the Fraunhofer IAIS Audio Mining system on Oral History interviews for the Digital Humanities Research. As an …...

AbstractThe advances of deep learning approaches in automatic speech recognition (ASR) and machine translation (MT) have allowed for levels of accuracy that move speech translation closer to being a commercially …...

In this paper, we describe the initial stages of our project, the goal of which is to create an integrated archive of the recordings, scanned documents, and photographs that would …...

AbstractA spoken language translation (ST) system consists of at least two modules: an automatic speech recognition (ASR) system and a machine translation (MT) system. In most cases, an MT is …...

AbstractInstructional videos get high-traffic on video sharing platforms, and prior work suggests that providing time-stamped, subtask annotations (e.g., “heat the oil in the pan”) improves user experiences. However, current automatic …...

This paper describes the development and first evaluation of the new Slovak children speech audio corpus for improving the automatic broadcast news subtitling engine developed on the Technical University of …...

AbstractFor automatic speech translation (AST), end-to-end approaches are outperformed by cascaded models that transcribe with automatic speech recognition (ASR), then trans- late with machine translation (MT). A major cause of …...

AbstractWe focus on the problem of language modeling for code-switched language, in the context of automatic speech recognition (ASR). Language modeling for code-switched language is challenging for (at least) three …...

The recent emergence of end-to-end automatic speech recognition (ASR) frameworks has streamlined the complicated modeling procedures of ASR systems in contrast to the conventional deep neural network-hidden Markov (DNN-HMM) ASR …...

AbstractAutomatic Speech Recognition (ASR) systems are increasingly powerful and more accurate, but also more numerous with several options existing currently as a service (e.g. Google, IBM, and Microsoft). Currently the …...

AbstractAutomatic speech recognition (ASR) systems are primarily evaluated on transcription accuracy. However, in some use cases such as subtitling, verbatim transcription would reduce output readability given limited screen size and …...

AbstractIn air traffic control, assistant systems support air traffic controllers in their work. To improve the reactivity and accuracy of the assistant, automatic speech recognition can monitor the commands uttered …...

AbstractModern digital personal assistants interact with users through voice. Therefore, they heavily rely on automatic speech recognition (ASR) in order to convert speech to text and perform further tasks. We …...

AbstractWe introduce the first attempt at automatic speech recognition (ASR) in Inuktitut, as a representative for polysynthetic, low-resource languages, like many of the 900 Indigenous languages spoken in the Americas. …...

AbstractThe Common Voice corpus is a massively-multilingual collection of transcribed speech intended for speech technology research and development. Common Voice is designed for Automatic Speech Recognition purposes but can be …...

AbstractWe introduce dual-decoder Transformer, a new model architecture that jointly performs automatic speech recognition (ASR) and multilingual speech translation (ST). Our models are based on the original Transformer architecture (Vaswani …...

AbstractDirectly translating from speech to text using an end-to-end approach is still challenging for many language pairs due to insufficient data. Although pretraining the encoder parameters using the Automatic Speech …...

AbstractELITR (European Live Translator) project aims to create a speech translation system for simultaneous subtitling of conferences and online meetings targetting up to 43 languages. The technology is tested by …...

AbstractDisfluency detection is usually an intermediate step between an automatic speech recognition (ASR) system and a downstream task. By contrast, this paper aims to investigate the task of end-to-end speech …...

AbstractWe evaluate several publicly available off-the-shelf (commercial and research) automatic speech recognition (ASR) systems across diverse dialogue domains (in US-English). Our evaluation is aimed at non-experts with limited experience in …...

AbstractIn this work, we present a detailed analysis of how accent information is reflected in the internal representation of speech in an end-to-end automatic speech recognition (ASR) system. We use …...

AbstractAutomatic speech recognition systems usually require large annotated speech corpus for training. The manual annotation of a large corpus is very difficult. It can be very helpful to use unsupervised …...

AbstractAutomatic Speech Recognition (ASR) is one of the most important technologies to support spoken communication in modern life. However, its development benefits from large speech corpus. The development of such …...

AbstractData-driven segmentation of words into subword units has been used in various natural language processing applications such as automatic speech recognition and statistical machine translation for almost 20 years. Recently …...

Communication is an important part of life. To use communication technology efficiently we need to know how to use them or how to instruct these devices to perform tasks. Automatic …...

AbstractThis paper surveys the first, three-year phase of a project at the National Research Council of Canada that is developing software to assist Indigenous communities in Canada in preserving their …...

AbstractSpoken language understanding tasks usually rely on pipelines involving complex processing blocks such as voice activity detection, speaker diarization and Automatic speech recognition (ASR). We propose a novel framework for …...

AbstractNatural language processing of conversational speech requires the availability of high-quality transcripts. In this paper, we express our skepticism towards the recent reports of very low Word Error Rates (WERs) …...

AbstractTransformer models have been used in automatic speech recognition (ASR) successfully and yields state-of-the-art results. However, its performance is still affected by speaker mismatch between training and test data. Further …...

Automatic speech recognition (ASR) in San- skrit is interesting, owing to the various lin- guistic peculiarities present in the language. The Sanskrit language is lexically productive, undergoes euphonic assimilation of …...

AbstractAutomatic Speech Recognition (ASR) technology presents the possibility for medical professionals to document patient record, diagnosis, postoperative care, patrol records, and etc. that are now done manually. However, earlier research …...

In this paper, we investigate the effect of layer freezing on the effectiveness of model trans- fer in the area of automatic speech recogni- tion. We experiment with Mozilla’s Deep- …...

AbstractWe propose a Transformer-based sequence-to-sequence model for automatic speech recognition (ASR) capable of simultaneously transcribing and annotating audio with linguistic information such as phonemic transcripts or part-of-speech (POS) tags. Since …...

AbstractThere has been increasing demand to develop effective computer-assisted language training (CAPT) systems, which can provide feedback on mispronunciations and facilitate second-language (L2) learners to improve their speaking proficiency through …...

Abstract“Transcription bottlenecks”, created by a shortage of effective human transcribers (i.e., transcriber shortage), are one of the main challenges to endangered language (EL) documentation. Automatic speech recognition (ASR) has been …...

In this paper, we describe the system team NSYSU-MITLab implemented for Formosa Speech Recognition Challenge 2020. We use the Transformer architecture  國立中山大學資訊工程學系 Department of Computer Science and Information Engineering …...

AbstractAutomatic Speech Recognition (ASR) systems are often optimized to work best for speakers with canonical speech patterns. Unfortunately, these systems perform poorly when tested on atypical speech and heavily accented …...

AbstractWhile Automatic Speech Recognition has been shown to be vulnerable to adversarial attacks, defenses against these attacks are still lagging. Existing, naive defenses can be partially broken with an adaptive …...

This paper describes the NTNU ASR system participating in the Formosa Speech Recognition Challenge 2020 (FSR-2020) supported by the Formosa Speech in the Wild project (FSW). FSR-2020 aims at fostering …...

AbstractDue to the surge in global demand for English as a second language (ESL), developments of automated methods for grading speaking proficiency have gained considerable attention. This paper aims to …...

AbstractWe investigate the exploitation of self-supervised models for two Creole languages with few resources: Gwadloupéyen and Morisien. Automatic language processing tools are almost non-existent for these two languages. We propose …...

AbstractThe usage of automatic speech recognition (ASR) systems are becoming omnipresent ranging from personal assistant to chatbots, home, and industrial automation systems, etc. Modern robots are also equipped with ASR …...

As voice user interfaces and conversational agents grow in importance, automatic speech recognition (ASR) encounters increasingly free-form and informal input data. Conversa- tional speech is at once the most challenging …...

AbstractWe evaluate several publicly available off-the-shelf (commercial and research) automatic speech recognition (ASR) systems on dialogue agent-directed English speech from speakers with General American vs. non-American accents. Our results show …...

AbstractThis paper seeks to improve the performance of automatic speech recognition (ASR) systems operating on code-switched speech. Code-switching refers to the alternation of languages within a conversation, a phenomenon that …...

AbstractSpeech is considered as a multi-modal process where hearing and vision are two fundamentals pillars. In fact, several studies have demonstrated that the robustness of Automatic Speech Recognition systems can …...

AbstractThis paper will introduce the use of Automatic Speech Recognition (ASR) technology to process speech content with specific domain. We will use the Conformer end-to-end model as the system architecture, …...

AbstractAutomatic Speech Recognition (ASR) is an efficient and widely used input method that transcribes speech signals into text. As the errors introduced by ASR systems will impair the performance of …...

AbstractTranscription is often reported as the bottleneck in endangered language documentation, requiring large efforts from scarce speakers and transcribers. In general, automatic speech recognition (ASR) can be accurate enough to …...

AbstractThis contribution presents our efforts to develop the automatic speech recognition (ASR) systems for three low resource languages: Kurmanji Kurdish, Cree and Inuktut. As a first step, we generate multilingual …...

. Interest in automatic closed captioning systems has risen on account of legal obli- gations concerning accessibility and the sheer amount of audiovisual content being produced by multiple sources. Such …...

AbstractRecent work has shown that systems for speech translation (ST) – similarly to automatic speech recognition (ASR) – poorly handle person names. This shortcoming does not only lead to errors …...

Language preservation has become increasingly urgent with globalization and rapid technological advancement. Minority languages, such as Hakka, are particularly vulnerable. This study aims to expedite the research and development of …...

In this study, we present a novel ap- proach to enhancing the performance of our Hakka Automatic Speech Recognition (ASR) model through the strategic use of Text-to-Speech (TTS) amplification tech- …...

AbstractThe performance of automatic speech recognition (ASR) systems has advanced substantially in recent years, particularly for languages for which a large amount of transcribed speech is available. Unfortunately, for low-resource …...

AbstractChinese Spelling Correction (CSC) is the task of detecting and correcting misspelled charac- ters in Chinese texts. As an important step for various downstream tasks, CSC confronts two challenges: 1) …...

Deep learning-based automatic speech recognition (ASR) design has been grow- ing in popularity. Besides the ASR model depends on the reliable speech representa- tion offered by the self-supervised learn- ing …...