Analysis of Emotion Recognition System for Telugu Using Prosodic and Formant Features

Mannepalli, Kasiprasad; Sastry, Panyam Narahari; Maloji, Suman

doi:10.1007/978-981-10-6626-9_15

Cited by 13 publications

(5 citation statements)

References 9 publications

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“…Under the control of DSP, the data is directly transmitted from the FIFO to the hard disk, which greatly improves the storage speed. Hard disk drive storage systems, control systems, and time series converters mainly use data obtained from the hard drive FIFO to perform various time conversions to meet read and write requirements (Mannepalli et al 2018). The literature shows that the design of an interactive audio system based on WIFI is very practical and has high practical significance (Mo and Niu 2017).…”

Section: Related Workmentioning

confidence: 99%

Application of Audio Technology of Internet of Things Based on Parallel Storage System in Music Classroom

Jiang

2023

Preprint

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Hard disk not only has powerful storage capacity, but also has highly intelligent interface and convenient application design. In daily life, hard disk is a very suitable tool for data collection and storage. The performance of hard disk is better when the number of samples is not too many, the sampling rate is low, and the number of sampling paths is small. However, when faced with some complex problems with high sampling rate and multiple paths, high-speed data storage will face greater difficulties. Therefore, this paper introduces a parallel storage system, and discusses the basic structure and the implementation of the system the factors that affect the storage rate, the specific structure of the data acquisition system in the system, which is subdivided into the structure of the power supply, data acquisition, caching and sorting and so on. With the support of parallel storage system, this paper summarizes some basic characteristics of audio, and focuses on the decisive role of hard disk in audio interactive system. In the process of research, it is found that the hardware system based on parallel storage system has many advantages, such as low consumption, small volume, high performance and low cost, which can achieve the research goal well. In recent years, the Internet of things has been widely used in many fields. Scientists have long explored the application of the Internet of things technology in the construction of contemporary mobile multimedia audio system, so that the multimedia video communication system can achieve intelligent development, and at the same time to realize its performance optimization, the price of the Internet of things audio technology can be reduced. In this paper, combined with the advantages of parallel storage system, the application of Internet of things audio technology in music classroom will be discussed to improve the efficiency of music teaching and students' music literacy.

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Section: Related Workmentioning

confidence: 99%

Application of Audio Technology of Internet of Things Based on Parallel Storage System in Music Classroom

Jiang

2023

Preprint

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“…Apart from these corpora, there are many more small speech databases created for emotion recognition purposes in Indo-Aryan and Dravidian languages [74][75][76][77].…”

Section: Emotional Speech Databases For Indo-aryan and Dravidianmentioning

confidence: 99%

A Review of the Advancement in Speech Emotion Recognition for Indo-Aryan and Dravidian Languages

Monisha

Sultana

2022

Advances in Human-Computer Interaction

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Speech emotion recognition (SER) has grown to be one of the most trending research topics in computational linguistics in the last two decades. Speech being the primary communication medium, understanding the emotional state of humans from speech and responding accordingly have made the speech emotion recognition system an essential part of the human-computer interaction (HCI) field. Although there are a few review works carried out for SER, none of them discusses the development of SER system for the Indo-Aryan or Dravidian language families. This paper focuses on some studies carried out for the development of an automatic SER system for Indo-Aryan and Dravidian languages. Besides, it presents a brief study of the prominent databases available for SER experiments. Some remarkable research works on the identification of emotion from the speech signal in the last two decades have also been discussed in this paper.

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“…A large and growing body of literature has investigated the influence of integrating prosodic information on the development of emotion and sentiment recognition systems. For instance, Meftah (2016) and Mannepalli (2018) extracted and compared some significant acoustic features from speech to determine the most significant acoustic feature that should be used in developing emotion recognition systems. Their results emphasised the importance of employing certain acoustic features in order to enhance the performance of these systems.…”

Section: Relationship To Previous Workmentioning

confidence: 99%

Developing a Stress Prediction Tool for Arabic Speech Recognition Tasks

Alsharhan¹,

Alnajem²

2021

SJKFU

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Developing natural language processing applications for Arabic must consider the different linguistic characteristics found in speech and translate those characteristics to script in order to reduce computational complexity and therefore reduce the word error rate (WER). Suprasegmental features are fundamental properties of speech that can enhance the performance of many natural speech processing applications. The present study considered stress as a prosodic feature comprising the prominence of syllables in speech by developing a tool that generated phonetic transcriptions and predicted the stress position. The generated transcription was used to create the phonetic dictionary necessary for developing an automatic speech recognition (ASR) system. This tool had to be accurate, linguistically motivated, and applicationally useful; therefore, the effectiveness of the generated stress-marked phonetic dictionary was tested by comparing the performance of a standard fixed dictionary-based system with that of one using the automatically generated dictionary. The research reported a 5.6% reduction in WER when using a dictionary with stress markers attached to each phone in the stressed syllable and a 3.5% reduction in WER when using a dictionary with stress markers assigned only to stressed vowels. These results encourage future studies to employ prosodic features of speech when developing different speech processing applications.

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Analysis of Emotion Recognition System for Telugu Using Prosodic and Formant Features

Cited by 13 publications

References 9 publications

Application of Audio Technology of Internet of Things Based on Parallel Storage System in Music Classroom

Application of Audio Technology of Internet of Things Based on Parallel Storage System in Music Classroom

A Review of the Advancement in Speech Emotion Recognition for Indo-Aryan and Dravidian Languages

Developing a Stress Prediction Tool for Arabic Speech Recognition Tasks

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