International Journal of Speech Technology

Aims & Scope

The International Journal of Speech Technology is a research journal that focuses on speech technology and its applications.

It promotes research and description on all aspects of speech input and output, including theory, experiment, testing, base technology, applications.

The journal is an international forum for the dissemination of research related to the applications of speech technology as well as to the technology itself as it relates to real-world applications.

Articles describing original work in all aspects of speech technology are included.

Sample topics include but are not limited to the following: applications employing digitized speech, synthesized speech or automatic speech recognition; technological issues of speech input or output; human factors, intelligent interfaces, robust applications; integration of aspects of artificial intelligence and natural language processing; international and local language implementations of speech synthesis and recognition; development of new algorithms; interface description techniques, tools and languages; testing of intelligibility, naturalness and accuracy; computational issues in speech technology; software development tools; speech-enabled robotics; speech technology as a diagnostic tool for treating language disorders; voice technology for managing serious laryngeal disabilities; the use of speech in multimedia.

View Aims & Scope

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Metrics & Ranking

SJR (SCImago Journal Rank)

Year	Value
2024	0.378

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	43

Journal Rank

Year	Value
2024	14338

Journal Citation Indicator

Year	Value
2024	727

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science and Social Sciences, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Emotion recognition from speech: a review

  Citation: 450

  Authors: Shashidhar G., K. Sreenivasa

• Databases, features and classifiers for speech emotion recognition: a review

  Citation: 268

  Authors: Monorama, Aurobinda, P.

• Feature extraction algorithms to improve the speech emotion recognition rate

  Citation: 175

  Authors: Anusha, Hima Bindu, Anil Kumar

• The German Text-to-Speech Synthesis System MARY: A Tool for Research, Development and Teaching

  Citation: 156

  Authors: Marc, Jürgen

• Emotion recognition from speech using global and local prosodic features

  Citation: 145

  Authors: K. Sreenivasa, Shashidhar G., Ramu Reddy

• Long short-term memory recurrent neural network architectures for Urdu acoustic modeling

  Citation: 116

  Authors: Tehseen, Usman

• A hybrid system for Parkinson’s disease diagnosis using machine learning techniques

  Citation: 104

  Authors: Rohit, Tarun, Hadeel Fahad, Anurag

• Vocal-based emotion recognition using random forests and decision tree

  Citation: 90

  Authors: Fatemeh, Tomasz, Dorota, Gholamreza

• Front end analysis of speech recognition: a review

  Citation: 81

  Authors: M. A., S. K.

• Speech enhancement with an adaptive Wiener filter

  Citation: 80

  Authors: Marwa A., Moawad I., Alaa M., Salaheldin M., El-Sayed M., Waleed, Saleh A., Fathi E.

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