Anomaly detection in voice conversations involve detection of unusual patterns, behavioral patterns and voice noise, anomaly points using statistical methods in an audio that is conversation between multiple speakers. It is a critical aspect of ensuring the reliability, security, and quality of communication systems. This project presents a comprehensive approach to detecting anomalies in voice conversations using advanced signal processing techniques and machine learning algorithms. Leveraging features such as Mel-frequency cepstral coefficients (MFCCs), spectral centroid, zero-crossing rate, and energy, the system extracts relevant information from audio data to characterize normal and abnormal speech patterns

• @Navuluri Balaji
• @Nithish Paidimarri

1.Open project in Visual Studio

2.Click on Terminal -> New Terminal

3.Type Python app.py in Terminal

4.Open Command Prompt

5.Type streamlit run app.py

Clone the project

  git clone https://github.com/NavuluriBalaji/Anomaly-Detection-in-Voice-Conversations

Go to the project directory

  cd my-project

Install dependencies

  npm install

Start the server

  npm run start

For support, email [email protected]