Inspiration

About the Project – SpeechAnalyticsAI

SpeechAnalyticsAI is an AI-powered speech analysis system developed to compare audio recordings and identify potential speech differences. The system analyzes audio features such as duration, energy, pitch, and silence to understand speech characteristics.

It uses Faster-Whisper for speech recognition and Librosa for audio feature extraction. The application generates word-level timestamps, compares recognized speech with a reference transcript, and highlights potential differences for further review.

An interactive Streamlit dashboard presents the analysis results through tables, charts, and downloadable CSV reports. It also supports manual audio evidence review, helping users record observations about possible speech issues.

The main goal of SpeechAnalyticsAI is to make speech analysis more efficient, understandable, and evidence-based. The system supports human verification rather than automatically treating every detected difference as a confirmed speech.

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Introducing SpeechAnalyticsAI – An AI-Powered Speech Analysis Project!

I'm excited to share the progress of my project, SpeechAnalyticsAI, developed for the Multimodal AI Hackathon 2026.

What I've built so far:

Good vs. Bad Audio Comparison Audio Feature Extraction using Librosa Silence Detection with Timestamps

  • Speech Recognition using Faster-Whisper
  • Transcript Comparison to identify potential speech differences
  • Interactive Dashboard using Streamlit
  • Downloadable CSV Reports and Manual Audio Review

Tech Stack: Python, Streamlit, Librosa, Faster-Whisper, Pandas, and Matplotlib.

This project aims to make speech analysis easier by combining audio signal analysis, speech recognition, and timestamp-based transcript review in one dashboard.

I'm continuing to improve the project and explore ways to make speech analysis more accurate and useful.

Every step is a learning experience!

SpeechAnalyticsAI #AI #Python #SpeechRecognition #AudioProcessing #MachineLearning #Hackathon2026 #Streamlit

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