A study on impact of language model in improving the accuracy of speech to text conversion system

Shivakumar, K. M.; Jain, Varsha; Priya, P. Krishna

doi:10.1109/iccsp.2017.8286557

Cited by 8 publications

(3 citation statements)

References 13 publications

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“…Shivakumar et al [11] conducted a study that delves into the influence of language models on enhancing the precision of speech-to-text conversion systems. It is a comprehensive analysis of the technologies employed in speech recognition systems with small, medium, and large vocabularies, while also assessing their respective advantages and drawbacks.…”

Section: Module 3: Speech To Text Conversionmentioning

confidence: 99%

“…It evaluates the benefits and limitations of different approaches and focuses on the role of language models in improving accuracy. The experiment involves testing speech data with noisy sentences and incomplete words, and the results show that randomly chosen sentences yield better accuracy compared to sequential sentences[11].Automatic Text Summarization can be categorized into extractive, abstractive, and hybrid approaches. Extractive methods select important sentences from the input document(s), while abstractive methods generate new sentences that convey the main ideas of the text.…”

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confidence: 99%

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Exploring Advances in Meeting Minutes Generation and Face Attendance Systems: A Comprehensive Literature Survey

Mane

2024

IJSREM

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The existing literature survey offers a thorough exploration of automatic text summarization, speech-to-text conversion, and face recognition technologies, all of which are integral to the proposed model named as ConvoLogix. Historically, traditional methods for managing meetings and collaboration involved manual note-taking and attendance tracking. These processes were time-consuming, error-prone, and not conducive to optimization. In today’s fast-paced business environment, the absence of automated solutions hinders efficiency and collaboration. The survey underscores the significance of embracing advanced techniques in Machine Learning with Traditional and Deep Learning Models for Audio and video processing for process automation, emphasizing their pivotal role in streamlining meetings and attendance tracking. A key theme within the survey is the identification of limitations associated with conventional approaches to meeting minute generation and attendance recording. The ConvoLogix model’s core objective is to leverage these technologies to automate meeting minutes generation and attendance tracking, resulting in time savings, improved collaboration, and data-driven insights. Key Words: Automated Meeting Summarization, Face Attendance Tracking, Natural Language Processing, Machine Learning, Deep Learning, Neural Network Models

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Section: Module 3: Speech To Text Conversionmentioning

confidence: 99%

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confidence: 99%

Exploring Advances in Meeting Minutes Generation and Face Attendance Systems: A Comprehensive Literature Survey

Mane

2024

IJSREM

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“…An effective method to gain fluency in English language that enhances the user's way of speech through correctness of pronunciation following the English phonetics was developed by Jose et al [1]. A comparative analysis mentioning the benefits and demerits of the various sizes of vocabulary speech recognition systems was done by Sivakumar et al [2]. This work demonstrated the role of language model in improving the accuracy of speech to text conversion with different scenarios with noises and broken words.…”

Section: Related Workmentioning

confidence: 99%

Speech to text conversion and summarization for effective understanding and documentation

Vinnarasu

Jose

2019

IJECE

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<p class="western" style="margin-top: 0.21cm; margin-bottom: 0cm;" align="justify"><span>Speech, is the most powerful way of communication with which human beings express their thoughts and feelings through different languages. The features of speech differs with each language. However, even while communicating in the same language, the pace and the dialect varies with each person. This creates difficulty in understanding the conveyed message for some people. Sometimes lengthy speeches are also quite difficult to follow due to reasons such as different pronunciation, pace and so on. Speech recognition which is an inter disciplinary field of computational linguistics aids in developing technologies that empowers the recognition and translation of speech into text. Text summarization extracts the utmost important information from a source which is a text and provides the adequate summary of the same. The research work presented in this paper describes an easy and effective method for speech recognition. The speech is converted to the corresponding text and produces summarized text. This has various applications like lecture notes creation, summarizing catalogues for lengthy documents and so on. Extensive experimentation is performed to validate the efficiency of the proposed method</span></p>

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Comprehensive Survey of Audio-to-Text Conversion

Parthasarathi,

Banu,

Joshi

2024

Smart Innovation, Systems and Technologies

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A study on impact of language model in improving the accuracy of speech to text conversion system

Cited by 8 publications

References 13 publications

Exploring Advances in Meeting Minutes Generation and Face Attendance Systems: A Comprehensive Literature Survey

Exploring Advances in Meeting Minutes Generation and Face Attendance Systems: A Comprehensive Literature Survey

Speech to text conversion and summarization for effective understanding and documentation

Comprehensive Survey of Audio-to-Text Conversion

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