---
title: "Speech analytics: Definition, Uses & Examples | Ringg AI"
description: "Understand Speech analytics and its role in better call outcomes. See how teams measure it, interpret results, and improve performance."
canonical_url: "https://www.ringg.ai/glossary/speech-analytics"
last_updated: "2026-09-22T13:01:52.000Z"
---

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Review information[![Parth Professional Headshot](https://images.prismic.io/ringg-ai/Kpm-xxgQMVGvgNce_ParthProfessionalHeadshot.JPG?auto=format%2Ccompress&w=640&fit=crop)

Parth Chadha Author

](https://www.ringg.ai/author/parth-chadha)[![Utkarsh Shukla](https://images.prismic.io/ringg-ai/uYgdBxNSatC9ji0Q_IMG-6.jpg?auto=format%2Ccompress&rect=0%2C1168%2C4672%2C4672&w=640&fit=crop)

Utkarsh Shukla Reviewer

](https://www.ringg.ai/author/utkarsh-shukla)

Last reviewed 22 Sep 2026

# What is Speech analytics?

Speech analytics uses transcription, acoustic signals, and language analysis to identify patterns, topics, sentiment, compliance events, and operational outcomes in calls.

Aliases

Speech analytics technology, call analytics

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Review information[![Parth Professional Headshot](https://images.prismic.io/ringg-ai/Kpm-xxgQMVGvgNce_ParthProfessionalHeadshot.JPG?auto=format%2Ccompress&w=640&fit=crop)

Parth Chadha Author

](https://www.ringg.ai/author/parth-chadha)[![Utkarsh Shukla](https://images.prismic.io/ringg-ai/uYgdBxNSatC9ji0Q_IMG-6.jpg?auto=format%2Ccompress&rect=0%2C1168%2C4672%2C4672&w=640&fit=crop)

Utkarsh Shukla Reviewer

](https://www.ringg.ai/author/utkarsh-shukla)

Last reviewed 22 Sep 2026

## Why is speech analytics important for improving call outcomes?

Speech analytics turns the content and acoustic qualities of conversations into evidence that teams can use to improve service, compliance, and automation.

*   Finds recurring topics, objections, and customer needs.
*   Identifies quality or compliance events across large call volumes.
*   Shows where agents and automated flows create friction.
*   Connects conversation patterns with resolution and business outcomes.

## How Speech analytics works

*   Audio is decoded, separated by speaker, and converted into a time-aligned transcript.
*   Language and acoustic models identify phrases, topics, silence, overlap, pace, and other speech events.
*   Rules or classifiers map those signals to QA, compliance, intent, and experience categories.
*   Analysts validate samples and aggregate results while keeping links to the underlying evidence.

## Speech analytics in action

A quality team searches every consented call for required disclosure language. Time-aligned matches show where the disclosure occurred, while reviewed false positives improve the rule before it becomes an automated compliance alert.

## How Speech analytics is measured or evaluated

Use a stable definition and representative production data. Review these measures together:

*   transcription and diarization accuracy on production audio
*   precision and recall for each topic or compliance rule
*   coverage of eligible audio and languages
*   reviewer agreement and alert confirmation rate

## Limitations, risks, and common failure modes

*   Recognition errors propagate into every downstream category.
*   Keyword spotting without context creates false compliance findings.
*   Speaker attribution errors can assign statements to the wrong person.
*   Broad transcript access can expose sensitive customer data.

## Speech analytics vs. conversational analytics

Speech analytics extracts information from spoken audio and transcripts. Conversational analytics adds dialogue structure, intent progression, outcomes, and cross-channel context.

## What teams should consider when using or implementing Speech analytics

*   Benchmark the actual codecs, languages, and noise conditions.
*   Attach evidence spans and confidence to every finding.
*   Use separate thresholds for discovery and enforcement.
*   Sample both positive and negative predictions.
*   Redact or restrict sensitive content before analysis.

## Sources

*   [What is speech analytics? | Definition from TechTarget](https://www.techtarget.com/enterprise-software/definition/speech-analytics)
*   [Speech Analytics | Technology Glossary Definitions | G2](https://www.g2.com/glossary/speech-analytics-definition)
*   [What is Speech Analytics? | TELUS Digital](https://www.telusdigital.com/glossary/speech-analytics)
*   [Amazon Connect metric definitions](https://docs.aws.amazon.com/connect/latest/adminguide/metrics-definitions.html)
*   [Ringg AI documentation](https://docs.ringg.ai/get-started/overview)

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## Related terms

*   [First contact resolution Understand First contact resolution and its role in resolution across support channels. See how teams measure it, interpret results, and improve performance.](https://www.ringg.ai/glossary/first-contact-resolution)
*   [Response time Understand Response time and its role in customer trust. See how teams measure it, interpret results, and improve performance.](https://www.ringg.ai/glossary/response-time)
*   [Deflection rate Understand Deflection rate and its role in self-service adoption measurement. See how teams measure it, interpret results, and improve performance.](https://www.ringg.ai/glossary/deflection-rate)
*   [Average handle time Understand Average handle time and its role in contact-center capacity planning. See how teams measure it, interpret results, and improve performance.](https://www.ringg.ai/glossary/average-handle-time)
*   [Average wait time Understand Average wait time and its role in better customer experience. See how teams measure it, interpret results, and improve performance.](https://www.ringg.ai/glossary/average-wait-time)
*   [Conversational analytics Understand Conversational analytics and its role in better automated customer journeys. See how teams measure it, interpret results, and improve performance.](https://www.ringg.ai/glossary/conversational-analytics)

Source: https://www.ringg.ai/glossary/speech-analytics
