Voice Control Music System Using Raspberry Pi

Year : 2025 | Volume : 15 | Issue : 02 | Page : 34 39
    By

    Prakash Kumar,

  • Deep Satish Jedhe,

  • Vijay H. Hovel,

  • Omkar S. Sindhe,

  1. Assistant Professor, Department of Electronics Telecommunication Engineering, Shri Chhatrapati Shivajiraje College of Engineering,, Maharashtra, India
  2. Student, Department of Electronics Telecommunication Engineering, Shri Chhatrapati Shivajiraje College of Engineering,, Maharashtra, India
  3. Student, Department of Electronics Telecommunication Engineering, Shri Chhatrapati Shivajiraje College of Engineering,, Maharashtra, India
  4. Student, Department of Electronics Telecommunication Engineering, Shri Chhatrapati Shivajiraje College of Engineering,, Maharashtra, India

Abstract

This paper presents a voice-controlled music system using Raspberry Pi, designed for hands-free music playback through voice commands. The system is implemented using Raspberry Pi 4B, a microphone, a speaker, and a 32GB SD card. The software is developed in Python using Thonny IDE, leveraging libraries such as SpeechRecognition, PyAudio, and gTTS for speech processing and audio playback. The system recognizes user commands like play, pause, next, and stop, converting speech input into text and executing corresponding actions. The Raspberry Pi serves as the main controller, interpreting voice commands via a microphone and playing music through connected speakers. It supports both locally stored files and streaming services, creating a smooth and interactive audio experience. This setup provides users with convenient, hands-free control over their music, enhancing accessibility and user engagement in smart audio systems. Performance evaluation includes voice recognition accuracy, response time, and real-time execution efficiency. Future enhancements include multilanguage support, noise reduction, and smart assistant integration. This work contributes to advancing voice-based Internet of Things (IoT) applications in entertainment and accessibility solutions.

Keywords: Voice recognition, Raspberry Pi 4B, speech-to-text processing, hands-free music control, IoT-based audio system

[This article belongs to Journal of VLSI Design Tools and Technology ]

How to cite this article:
Prakash Kumar, Deep Satish Jedhe, Vijay H. Hovel, Omkar S. Sindhe. Voice Control Music System Using Raspberry Pi. Journal of VLSI Design Tools and Technology. 2025; 15(02):34-39.
How to cite this URL:
Prakash Kumar, Deep Satish Jedhe, Vijay H. Hovel, Omkar S. Sindhe. Voice Control Music System Using Raspberry Pi. Journal of VLSI Design Tools and Technology. 2025; 15(02):34-39. Available from: https://journals.stmjournals.com/jovdtt/article=2025/view=224329


References

  1. Seth A, Ray N, Paul A, Bag P, Sarkar S, Das KS, et al. Raspberry Pi controlled automated residential system with integrated Alexa Voice Service. 2024 IEEE 1st International Conference on Green Industrial Electronics and Sustainable Technologies (GIEST), Imphal, India. 2024. p. 1–6. doi:10.1109/GIEST62955.2024.10960058.
  2.  Irugalbandara C, Naseem AS, Perera S, Kiruthikan S, Logeeshan V. A secure and smart home automation system with speech recognition and power measurement capabilities. Sensors. 2023;23:5784. doi:10.3390/s23135784. PMID: 37447635.
  3. Groenli TM, Flesch B, Mukkamala R, Vatrapu R, Klavestad S, Bergner H. Internet of things big data analytics: The case of noise level measurements at the Roskilde music festival. 2018 IEEE International Conference on Big Data (Big Data), Seattle, WA, USA. 2018. p. 5153–8. doi:10.1109/BigData.2018.8622406.
  4.  Revathi A, Sasikaladevi N, Arunprasanth D, Raju N. Raspberry Pi-based robust speech command recognition for normal and hearing-impaired (HI). Multimed Tools Appl. 2024;83:51589–613. doi:10.1007/s11042-023-17543-8.
  5.  Prasanna G, Ramadass N. Low cost home automation using offline speech recognition. Int J Signal Process Syst. 2014;2:96–101.
  6. Marot J, Bourennane S. Raspberry Pi for image processing education. 2017 25th European Signal Processing Conference (EUSIPCO), Kos, Greece. 2017. p. 2364–2366. doi:10.23919/EUSIPCO. 2017.8081633.
  7. Kasundra CT, Shirsat AS. Raspberry-Pi based health monitoring system. Int J Adv Res Electr Electron Instrum Eng. 2015;4:7147–54. doi: 10.15662/ijareeie.2015.0408083.
  8.  Boruah AN, Goswami M, Kumar M, Loyola-González O, editors. Embedded Artificial Intelligence: Real-Life Applications and Case Studies. Boca Raton, Fla., USA: Chapman and Hall/CRC; 2025. doi:10.1201/9781003481089.
  9. Mi Suresh S, Rao YS. Modelling of secured voice recognition based automatic control system. Int J Emerg Technol Comput Sci Electron. 2015;13:140–4.
  10. Washani N, Sharma S. Speech recognition system: A review. Int J Comput Appl. 2015;115:7–10. doi:10.5120/20249-2617.
Regular Issue Subscription Original Research
Volume 15
Issue 02
Received 17/04/2025
Accepted 08/05/2025
Published 21/08/2025
Publication Time 126 Days
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