Speech Analytics Software for Call Monitoring and Quality Reviews
- Arcitech
- 19th October 2026
A dashboard says every call has been analyzed. Yet transferred conversations are missing, one language produces unreliable transcripts and supervisors cannot explain why an agent received a low score.
The system processed a large volume of audio. That does not establish complete or dependable monitoring.
Speech analytics software converts recorded or live conversations into searchable transcripts, categories and evaluation signals. Monitoring every eligible call requires reliable recording, processing, validation and review not simply switching on transcription.
For contact centre leaders, coverage and accuracy need separate definitions and separate measurements.
The system processed a large volume of audio. That does not establish complete or dependable monitoring.
Speech analytics software converts recorded or live conversations into searchable transcripts, categories and evaluation signals. Monitoring every eligible call requires reliable recording, processing, validation and review not simply switching on transcription.
For contact centre leaders, coverage and accuracy need separate definitions and separate measurements.
What Does Speech Analytics Software Do
Speech analytics software combines speech recognition with analysis of conversation content and characteristics.
Depending on the platform, it can identify contact reasons, search for phrases, flag possible policy issues and support quality evaluations.
AWS documentation, for example, describes conversational analytics capabilities including sentiment analysis, conversation characteristics and automated population of evaluation forms.
These are configurable capabilities rather than proof that every assessment is correct.
Call analytics software may also include operational measures such as call volumes, routing and handling times. Speech analytics adds interpretation of what happened within the conversation.
Depending on the platform, it can identify contact reasons, search for phrases, flag possible policy issues and support quality evaluations.
AWS documentation, for example, describes conversational analytics capabilities including sentiment analysis, conversation characteristics and automated population of evaluation forms.
These are configurable capabilities rather than proof that every assessment is correct.
Call analytics software may also include operational measures such as call volumes, routing and handling times. Speech analytics adds interpretation of what happened within the conversation.
Define What 100 Percent of Calls Means
Before evaluating software, define the denominator.
Does the claim cover all connected customer calls, only recorded calls or only calls that meet processing requirements? Are transfers counted as separate segments or one customer interaction?
These distinctions matter because a high processing rate can hide missing recordings.
Track coverage through successive stages:
Report exclusions openly. A call excluded because recording was unavailable should remain visible as a coverage gap.
Does the claim cover all connected customer calls, only recorded calls or only calls that meet processing requirements? Are transfers counted as separate segments or one customer interaction?
These distinctions matter because a high processing rate can hide missing recordings.
Track coverage through successive stages:
| Stage | What to verify |
|---|---|
| Eligible interactions | Which calls should be monitored under the agreed scope |
| Recording captured | Whether usable audio exists |
| Processing completed | Whether analysis finished successfully |
| Required checks completed | Whether applicable evaluation questions were assessed |
| Exceptions reviewed | Whether flagged issues reached an owner |
What Full Call Monitoring Requires
Reliable Recording Across Every Call Path
Map inbound calls, outbound calls, transfers and queue changes.
Recording and analytics settings may differ between flows. AWS documentation specifically notes that continuing analytics after a transfer requires appropriate configuration in the transfer flow.
Test actual journeys rather than checking configuration alone. Include dropped connections, transfers between teams and conversations with several participants.
. Define recording permissions, notices, retention and access according to the applicable requirements.
Recording and analytics settings may differ between flows. AWS documentation specifically notes that continuing analytics after a transfer requires appropriate configuration in the transfer flow.
Test actual journeys rather than checking configuration alone. Include dropped connections, transfers between teams and conversations with several participants.
. Define recording permissions, notices, retention and access according to the applicable requirements.
Processing That Detects Its Own Failures
Every eligible recording needs a processing status.
Unsupported configurations, audio-format issues or other failures can prevent analysis. AWS documents error notifications for contacts that cannot be analysed, including invalid language settings and unsupported recording characteristics. [3]
Create alerts, retry rules and recovery ownership. Reconcile completed analyses against expected interactions so failed jobs do not disappear from reporting.
Unsupported configurations, audio-format issues or other failures can prevent analysis. AWS documents error notifications for contacts that cannot be analysed, including invalid language settings and unsupported recording characteristics. [3]
Create alerts, retry rules and recovery ownership. Reconcile completed analyses against expected interactions so failed jobs do not disappear from reporting.
Transcription Tested on Real Calls
A readable transcript can still contain errors that change the meaning of a conversation.
Build a test set covering relevant languages, accents, products and recording conditions. Include overlapping speech, names, reference numbers and industry terminology.
Microsoft documents quantitative evaluation of speech recognition using reference transcripts and word error rate. This provides one measure of transcription quality. [4]
Also test business-critical phrases directly. Missing a negation in “the payment was not authorised” can matter more than several harmless transcription errors elsewhere.
Build a test set covering relevant languages, accents, products and recording conditions. Include overlapping speech, names, reference numbers and industry terminology.
Microsoft documents quantitative evaluation of speech recognition using reference transcripts and word error rate. This provides one measure of transcription quality. [4]
Also test business-critical phrases directly. Missing a negation in “the payment was not authorised” can matter more than several harmless transcription errors elsewhere.
Evaluation Criteria With Clear Evidence
Translate quality standards into questions that reviewers can assess consistently.
“Was the agent professional?” leaves considerable room for interpretation. A narrower question—such as whether the agent explained the agreed next action—can be tested against specific evidence.
Consider a hypothetical cancellation call. A customer asks about cancellation charges, but the system categorizes the conversation as a completed cancellation.
The workflow should distinguish discussion, intent and completed action. Validate the result against the transcript and relevant system records before using it for reporting.
“Was the agent professional?” leaves considerable room for interpretation. A narrower question—such as whether the agent explained the agreed next action—can be tested against specific evidence.
Consider a hypothetical cancellation call. A customer asks about cancellation charges, but the system categorizes the conversation as a completed cancellation.
The workflow should distinguish discussion, intent and completed action. Validate the result against the transcript and relevant system records before using it for reporting.
Human Review and Calibration
AI speech analytics can screen conversations at scale, while reviewers validate uncertain findings and consequential scores.
Use human-in-the-loop AI where a result may affect an employee assessment, customer complaint or sensitive investigation.
Compare automated results with calibrated human evaluations. Record disagreements and investigate whether they arise from transcription, unclear criteria or missing context.
Review unflagged calls too. Examining only alerts cannot reveal issues the system failed to detect.
Use human-in-the-loop AI where a result may affect an employee assessment, customer complaint or sensitive investigation.
Compare automated results with calibrated human evaluations. Record disagreements and investigate whether they arise from transcription, unclear criteria or missing context.
Review unflagged calls too. Examining only alerts cannot reveal issues the system failed to detect.
Benefits Beyond Broader Coverage
More Focused Quality Reviews
Search and screening can help analysts locate conversations relevant to a complaint, process change or coaching need.
Better Understanding of Contact Reasons
Consistent categorization can reveal recurring questions and avoidable customer effort. Validate categories before treating trends as established facts.
Faster Follow Up
A detected issue can create a task with the relevant conversation evidence. Value depends on whether the task is resolved, not merely generated.
More Specific Coaching
Evidence-linked findings can support practical coaching. Supervisors should explain the behaviour and its context rather than relying on an unexplained score.
Risks and Tradeoffs
Sentiment Is Not a Performance Verdict
A customer may remain unhappy because of a product failure even when an agent handles the call appropriately. Interpret sentiment alongside the conversation and outcome.
Excessive Alerts Create Review Backlogs
Broad criteria may flag routine conversations. Monitor how many alerts reviewers confirm and refine checks that generate unnecessary work.
Sensitive Information Needs Controlled Access
Set permissions for recordings, transcripts and exports. Where redaction is used, validate its effectiveness rather than assuming every sensitive detail is removed.
Expanded Coverage Adds Costs
Include transcription, storage, analysis, integrations and reviewer time. More processed calls do not automatically produce better service.
Implement in Stages and Measure Results
Pilot representative queues before expanding. Test coverage failures and evaluation accuracy separately.
Define sampling methods and calculation rules so results remain comparable.
| KPI | What it reveals |
|---|---|
| Recording coverage | Eligible interactions with usable audio |
| Analysis completion rate | Captured calls successfully processed |
| Evaluation completion rate | Applicable checks completed |
| Alert precision | Flagged issues confirmed by reviewers |
| Missed-issue rate | Issues found through review that screening missed |
| Review turnaround | Time from detection to an assessed finding |
| Corrective-action completion | Whether confirmed findings lead to action |
Make Coverage a Verifiable Claim
Speech analytics software can expand monitoring, but dependable results require evidence at every stage.
Start with a clear scope, test representative calls and retain review routes for uncertain findings.
Arcitech’s published AI automation services describe a BPO Box quality-monitoring project using speech analytics and sentiment detection. A relevant project discussion should establish recording access, coverage definitions and evaluation requirements before setting performance targets. [5]
Start with a clear scope, test representative calls and retain review routes for uncertain findings.
Arcitech’s published AI automation services describe a BPO Box quality-monitoring project using speech analytics and sentiment detection. A relevant project discussion should establish recording access, coverage definitions and evaluation requirements before setting performance targets. [5]
Turn Customer Conversations into Actionable Insights
Analyse customer calls at scale, identify recurring issues, and support quality monitoring with AI-powered insights that help teams improve service.
Frequently Asked Questions
1. Can speech analytics software analyse every call?
Potentially every eligible call, provided recording, language support, configuration and processing requirements are met. Coverage needs verification.
2. Is transcription the same as quality monitoring?
No. Transcription produces text. Quality monitoring evaluates defined behaviours, evidence and outcomes.
3. Does AI speech analytics replace quality analysts?
It can support screening and evaluation. Analysts remain important for calibration, disputed findings and contextual review.
4. What should a contact centre test first?
Verify recording coverage, representative transcription quality and a small set of clearly defined evaluation criteria.
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