# Audio Silence Map

Output silence intervals as JSON and CSV

> Canonical page: https://elysiatools.com/en/tools/audio-silence-map

- **Category:** Media

- **Keywords:** audio, silence, map, csv, json, analysis

## Overview

Runs FFmpeg silencedetect and returns a JSON list plus a CSV map.

## Inputs

- **Audio File** (file): Select an audio file
- **Silence Threshold (dB)** (number): -50
- **Minimum Silence Duration (s)** (number): 0.5

## When to use

- When you need to identify and map silent sections in audio recordings for editing or trimming.
- For analyzing audio files to ensure compliance with silence standards in broadcasting or production.
- To automate the detection of pauses in podcasts, lectures, or interviews for efficient post-processing.

## How it works

- Upload your audio file in a supported format (e.g., MP3, WAV).
- Optionally adjust the silence threshold (in dB) and minimum silence duration (in seconds).
- The tool processes the file with FFmpeg silencedetect and outputs a JSON list and CSV map of silence intervals.

## Use cases

- Editing podcasts to remove long silent pauses and improve flow.
- Quality assurance in audio production to detect unintended silence.
- Academic research analyzing speech patterns by identifying pauses in recordings.

## Frequently asked questions

### What audio file formats are supported?

The tool supports common audio formats like MP3, WAV, and others compatible with FFmpeg.

### How do I set the silence detection sensitivity?

Adjust the Silence Threshold (dB) and Minimum Silence Duration (s) parameters to control what is considered silent.

### What does the output look like?

You receive a JSON array of objects with start and end times, and a CSV file with similar data for easy import into spreadsheets.

### Is there a limit on audio file size?

Yes, the audio file must be under 200 MB as per the tool's file limit.

### Can I use this tool for real-time audio processing?

No, this tool is designed for offline analysis of uploaded audio files.

## Related tools

- [Audio Chord Progression Detector](https://elysiatools.com/en/tools/audio-chord-progression-detector): Estimate an audio file's chord sequence locally and download CSV, JSON, SVG, and method notes in one ZIP.
- [Audio Voice Activity Segmentation](https://elysiatools.com/en/tools/audio-voice-activity-segmentation): Detect likely speech-range activity and export speech/non-speech ranges as JSON, CSV, SRT markers, or an FFmpeg cut list.
- [Structured Log Analyzer](https://elysiatools.com/en/tools/structured-log-analyzer): Detect common log formats, extract core fields, infer field types, and export parsed logs as JSON, CSV, or SQL inserts
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- [Dataset Imbalance Detector & Resampler](https://elysiatools.com/en/tools/dataset-imbalance-detector-resampler): Detect class imbalance in CSV or JSON datasets, compare resampling strategies, and preview a balanced output dataset
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- [Train/Test Split with Stratification](https://elysiatools.com/en/tools/train-test-split-with-stratification): Class-stratified train/validation/test split or stratified k-fold for CSV/JSON datasets — seeded, reproducible, with distribution reports, leakage checks, SMOTE preview and CSV export.

## Samples

- [CSV Samples](https://elysiatools.com/en/samples/csv-samples): Sample CSV files with various data types, sizes, and complexity levels
- [Python Samples](https://elysiatools.com/en/samples/python): Essential Python code examples and Hello World demonstrations
- [ELK Stack Log Analysis Samples](https://elysiatools.com/en/samples/elk-stack-samples): Comprehensive ELK Stack (Elasticsearch, Logstash, Kibana) samples for log aggregation, processing, and visualization in distributed systems
- [WebRTC Real-Time Communication Samples](https://elysiatools.com/en/samples/webrtc-samples): Comprehensive WebRTC samples for peer-to-peer audio/video communication, data channels, screen sharing, and signaling server implementation
