Speech-to-Speech Translation: A Review

Dureja, Mahak; Gautam, Sumanlata

doi:10.5120/ijca2015907079

Cited by 3 publications

(2 citation statements)

References 5 publications

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“…4;2017 Speech-to-Speech Translation of low-resource languages on mobile devices (Gao, et al, 2006).The general structure of MASTOR system has the components of ASR, MT and TTS. This pipelining approach allows system for the deployment of the existing speech and language handing out techniques, while taking care of unique problems in Speech-to-Speech Translation (Dureja and Gautam, 2015) Grapheme based acoustic models are used to overcome the problem of absence of short vowels Grapheme based acoustic model lead to unambiguous pronunciation of lexicons and hence facilitates the model training and decoding. Also, depending on its context the same grapheme may yield different phonetic sound and lead to less accurate acoustic models.…”

Section: Ibm's Mastormentioning

confidence: 99%

“…For example, Verb Mobil corpus has the chance that 20% of all dialog turns having at least one auto-correction and 3% also include false starts. A combined approach for deep and shallow analysis methods is used by this system to find out the slips in the speech and then translate it in accordance to what the person tried to say rather than what was actually said by him (Dureja and Gautam, 2015) …”

Section: Verbmobilmentioning

confidence: 99%

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An Investigation into Methodology and Metrics Employed to Evaluate the (Speech-to-Speech) Way in Translation Systems

Dashtaki¹

2017

MAS

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Speech-to-speech translation is a challenging problem, due to poor sentence planning typically associated with spontaneous speech, as well as errors caused by automatic speech recognition. Based upon a statistically trained speech translation system, in this study, we try to investigate methodologies and metrics employed to assess the (speech-to-speech) way in translation systems. The speech translation is performed incrementally based on generation of partial hypotheses from speech recognition. Speech-input translation can be properly approached as a pattern recognition problem by means of statistical alignment models and stochastic finite-state transducers. Under this general framework, some specific models are presented. One of the features of such models is their capability of automatically learning from training examples. The speech translation system consists of three modules: automatic speech recognition, machine translation and text to speech synthesis. Many procedures for incorporation of speech recognition and machine translation have been projected. In this research, we want explore methodologies and metrics employed to assess the (speech-to-speech) way in translation systems.

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Section: Ibm's Mastormentioning

confidence: 99%

Section: Verbmobilmentioning

confidence: 99%

An Investigation into Methodology and Metrics Employed to Evaluate the (Speech-to-Speech) Way in Translation Systems

Dashtaki¹

2017

MAS

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Real-time speech recognition of arabic language

Raheem¹,

Zuhair

2023

AIP Conference Proceedings

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Voice to Text Conversion using Deep Learning

Azhagusundaram,

Naveen,

Ganesh

et al. 2024

International Journal of Innovative Science and Research Techno

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Speech recognition is one of the quick developing engineering innovation. It has numerous applications in different areas, and offers numerous potential benefits. Numerous individuals might not communicate due to the dialect obstruction. Our objective is to diminish this boundary with our program planned and created to get to the framework in particular cases, giving crucial help in empowering individuals to share data by working the framework utilizing voice input May. This venture takes that calculate under consideration and endeavors to guarantee that our program recognizes discourse and changes over the input sound to content; This empowers the client to perform record operations such as spare, open, or select out of voice-only input. We plan a framework that recognizes human voices and sound clips and interprets between English and English. The yield is in content arrange and we offer choices to change over the sound from one dialect to another. Following, we trust to include a work that gives word reference implications for English words. Neural machine interpretation is the essential strategy utilized to perform machine interpretation within the industry. This work on discourse acknowledgment starts with an presentation to the innovation and its applications in different areas. Portion of the report is based on computer program enhancements in speech recognition.

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Speech-to-Speech Translation: A Review

Cited by 3 publications

References 5 publications

An Investigation into Methodology and Metrics Employed to Evaluate the (Speech-to-Speech) Way in Translation Systems

An Investigation into Methodology and Metrics Employed to Evaluate the (Speech-to-Speech) Way in Translation Systems

Real-time speech recognition of arabic language

Voice to Text Conversion using Deep Learning

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