Research on the application of Python language in audio processing and speech recognition Graduation project proposal report

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Research on the Application of Python Language in Audio Processing and Speech Recognition for College Students Graduation Project Proposal

1. Research background and significance

In the era of digitalization and informationization, audio processing and speech recognition technology have become an important part of human-computer interaction. Audio processing is the process of analyzing, transforming, and processing audio signals to improve sound quality, extract features, or achieve specific audio effects. Speech recognition is the process of converting human speech into text or commands, providing the basis for intelligent voice interaction.

As a powerful, easy-to-learn and easy-to-use programming language, Python has been widely used in the fields of audio processing and speech recognition. Its rich libraries and frameworks, such as librosa, pydub, TensorFlow, PyTorch, etc., provide powerful support for audio processing and speech recognition. Therefore, this study aims to explore the application of Python in audio processing and speech recognition, and provide valuable reference for research and development in related fields.

2. Research status at home and abroad

In terms of audio processing, domestic and foreign researchers have achieved rich results. Domestic researchers mainly focus on audio signal noise reduction, feature extraction, audio classification, etc., while foreign researchers are more focused on the application of deep learning, neural networks and other technologies in audio processing. In terms of speech recognition, with the development of deep learning technology, speech recognition methods based on deep learning have become mainstream, and domestic and foreign researchers are actively exploring and improving related algorithms and technologies.

However, there are still some problems in the field of audio processing and speech recognition, such as the low efficiency of audio processing algorithms and the need to improve recognition accuracy. Therefore, this research will start from the perspective of Python language, deeply explore the key technologies of audio processing and speech recognition, and try to propose innovative solutions.

3. Research ideas and methods

This research will adopt a research method that combines theory and practice, including the following steps:

1. Literature review: Systematically review the current research status and development trends of Python in the field of audio processing and speech recognition at home and abroad, and analyze the existing problems and deficiencies in existing research.

2. Technical research: Investigate and analyze Python's related libraries and frameworks in the fields of audio processing and speech recognition, and evaluate their advantages, disadvantages, and applicable scenarios.

3. Algorithm research: Conduct in-depth research and exploration on key technologies of audio processing and speech recognition, such as noise reduction, feature extraction, classification, recognition, etc., and propose innovative algorithms and solutions.

4. System implementation: Based on the Python language and related libraries and frameworks, a prototype system for audio processing and speech recognition is implemented, including the design and implementation of front-end and back-end functions.

5. Experimental verification: Verify the effectiveness and performance of the algorithms and solutions proposed in this study through experiments, and compare and analyze them with other existing methods.

4. Research content and innovation points

The research content of this study includes the application of Python in audio processing and speech recognition, research on key algorithms and technologies, and the design and implementation of prototype systems. The innovation lies in:

1. In-depth exploration of the application potential of Python in the field of audio processing and speech recognition, analyzing its advantages, disadvantages and applicable scenarios.

2. Propose innovative audio processing and speech recognition algorithms and solutions to improve processing efficiency and recognition accuracy.

3. Based on the Python language and related libraries and frameworks, a complete audio processing and speech recognition prototype system is implemented, providing a valuable reference for subsequent research and development.

5. Detailed introduction of front and back functions

Front-end functions will include user interaction interface design, task submission and result display, etc. Users can select audio files, set processing parameters, submit processing tasks, and view processing and recognition results in real time through the interface.

Background functions will include audio file reading and processing, feature extraction and classification, speech recognition and conversion, etc. Efficient algorithms and technologies will be used in the background to process and analyze audio files, extract key features, classify and identify them. At the same time, the backend will also be responsible for task scheduling and management to ensure the stability and efficiency of the system.

6. Research ideas, research methods, and feasibility

This study adopts research ideas and methods that combine theoretical analysis and practical verification, and explores its potential and advantages in the fields of audio processing and speech recognition through in-depth research and application of the Python language and related technologies. At the same time, this research will make full use of existing computing resources and open source libraries and frameworks to reduce research costs and difficulties, and improve the feasibility and practicality of research. After sufficient research and preparation, this research team has the ability and confidence to complete this topic.

7. Research progress arrangement

1. The first stage (2 months): Complete the literature review and technical research;
2. The second stage (3 months): Carry out algorithm research and experimental verification;
3. The third stage (4 months): Complete the design and implementation of the prototype system;
4. The fourth stage (2 months): System testing and performance evaluation;
5. The fifth stage (1 month): Organize research results and complete thesis writing.

8. Thesis (design) writing outline

1. Introduction: Explain the background and significance of the research, and propose the research questions and objectives;
2. Review of related technologies: Introducing the current application status of Python language in audio processing and speech recognition;
3. Research methods: Detailed description of research ideas and methods, including algorithm research and experimental verification;
4. Research results and analysis: Present research results and data analysis results;
5. Discussion and conclusion: discuss and summarize the research results;
6. References: List references and related materials.