{"id":3550,"date":"2026-09-11T05:20:54","date_gmt":"2026-09-11T05:20:54","guid":{"rendered":"https:\/\/www.plura.ai\/articles\/voicemail-detection-timeout-settings"},"modified":"2026-09-11T05:21:39","modified_gmt":"2026-09-11T05:21:39","slug":"voicemail-detection-timeout-settings","status":"publish","type":"post","link":"https:\/\/www.plura.ai\/articles\/voicemail-detection-timeout-settings","title":{"rendered":"How to Configure Voicemail Detection Timeout Settings"},"content":{"rendered":"<p><em>Written by: Matt Beucler, CEO, Plura AI<\/em><\/p>\n<p><em>Updated 2026-09-10<\/em><\/p>\n<h2 id=\"key-takeaways\">Key Takeaways<\/h2>\n<ul>\n<li>Voicemail detection timeout settings differ across platforms. Twilio and Vapi default to 30 seconds, while LiveKit uses 20 seconds and several vendors do not publish their values.<sup data-disclaimer-id=\"25\" data-disclaimer-index=\"4\">4<\/sup><\/li>\n<li>The four threshold categories (overall detection timeout, speech threshold, speech end or silence threshold, and initial silence timeout) govern different phases of call audio and require separate configuration.<\/li>\n<li>Short timeouts create three failure modes: more unknown results, broken message-end detection, and live humans routed to voicemail drops.<\/li>\n<li>Unit discipline matters. Twilio uses seconds for the overall timeout and milliseconds for speech and silence thresholds, so unit mistakes cause severe misconfiguration.<\/li>\n<li>Plura AI\u2019s AI Predictive Dialer handles voicemail detection natively on its own FCC-licensed carrier, which removes much of the parameter-guessing required by API-wrapper tools. <a href=\"https:\/\/www.plura.ai\/plura-webchat\" target=\"_blank\">See how Plura handles voicemail detection in a live demo<\/a>.<\/li>\n<\/ul>\n<h2>How to Read the Voicemail Detection Timeout Settings Comparison Table<\/h2>\n<p>The table below maps each platform to its primary answering machine detection (AMD) timeout parameter, its published default, and its valid range. Parameter names appear as inline code. Every value traces to that vendor\u2019s published documentation. When a platform\u2019s default is not published in public documentation, the table calls that out directly.<\/p>\n<table>\n<thead>\n<tr>\n<th>Platform<\/th>\n<th>Parameter Name<\/th>\n<th>Default<\/th>\n<th>Valid Range<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Twilio<\/td>\n<td><code>MachineDetectionTimeout<\/code><\/td>\n<td>30 seconds<\/td>\n<td>3\u201359 seconds<\/td>\n<\/tr>\n<tr>\n<td>Vapi<\/td>\n<td><code>machineDetectionTimeout<\/code><\/td>\n<td><a href=\"https:\/\/callsphere.ai\/blog\/voicemail-detection-accuracy-callsphere-vs-vapi\" target=\"_blank\" rel=\"noindex nofollow\">30 seconds (mirrors Twilio AMD defaults)<\/a><\/td>\n<td>Not independently published; delegates to Twilio AMD<\/td>\n<\/tr>\n<tr>\n<td>Retell<\/td>\n<td>Not published in public documentation<\/td>\n<td>Not published<\/td>\n<td>Not published<\/td>\n<\/tr>\n<tr>\n<td>LiveKit<\/td>\n<td>Not published as a single named parameter<\/td>\n<td>20-second timeout; 2.5-second human speech threshold<\/td>\n<td>Not published as a discrete range<\/td>\n<\/tr>\n<tr>\n<td>Pipecat<\/td>\n<td>Pipeline-level; no single vendor-defined parameter<\/td>\n<td>Not published<\/td>\n<td>Not published; configured at the transport or pipeline layer<\/td>\n<\/tr>\n<tr>\n<td>Amazon Connect<\/td>\n<td><code>RingTimeoutInSeconds<\/code> (ring timeout); AMD via <code>AnswerMachineDetectionConfig<\/code><\/td>\n<td>60 seconds (ring timeout default); AMD timeout not published<\/td>\n<td>15\u201360 seconds (ring timeout)<\/td>\n<\/tr>\n<tr>\n<td>Bland AI<\/td>\n<td>Not published in public documentation<\/td>\n<td>Not published<\/td>\n<td>Not published<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><a href=\"https:\/\/plura.ai\/pricing\" target=\"_blank\">Compare plans and rates side by side<\/a>.<\/p>\n<h2>How to Configure the Four Voicemail Detection Threshold Categories<\/h2>\n<p>Twilio\u2019s AMD documentation defines four distinct threshold categories. Each category controls a different phase of the call audio, so mixing them up creates avoidable errors.<\/p>\n<h3>Overall Detection Timeout<\/h3>\n<p>This setting is the hard deadline for the AMD decision. On Twilio, <code>MachineDetectionTimeout<\/code> defaults to 30 seconds, with a valid range of 3\u201359 seconds. If the deadline fires before a verdict, Twilio returns <code>AnsweredBy=unknown<\/code>. LiveKit\u2019s equivalent timeout defaults to 20 seconds. Vapi mirrors Twilio\u2019s 30-second default when routing through Twilio AMD. Retell, Pipecat, Bland AI, and Amazon Connect\u2019s AMD-specific timeout do not publish equivalent values.<\/p>\n<h3>Speech Threshold (~2400 ms)<\/h3>\n<p>This parameter defines the minimum duration of continuous speech that triggers a machine classification. On Twilio, <code>MachineDetectionSpeechThreshold<\/code> defaults to 2400 ms, with a valid range of 1000\u20136000 ms. Speech shorter than the threshold may classify as human, while longer speech may classify as machine. Vapi\u2019s published configuration examples <a href=\"https:\/\/callsphere.ai\/blog\/voicemail-detection-accuracy-callsphere-vs-vapi\" target=\"_blank\" rel=\"noindex nofollow\">use the same 2400 ms default<\/a>. LiveKit\u2019s equivalent is 2.5 seconds. Retell, Pipecat, Bland AI, and Amazon Connect do not publish this value.<\/p>\n<h3>Speech End or Silence Threshold (1200\u20135000 ms)<\/h3>\n<p>This parameter defines how much silence must follow a speech segment before the system treats that segment as complete. On Twilio, <code>MachineDetectionSpeechEndThreshold<\/code> defaults to 1200 ms, with a valid range of 500\u20135000 ms. Twilio recommends increasing this to about 2500 ms to handle short voicemail greetings that pause mid-greeting, and notes that higher values add equivalent delay to human detection. Vapi\u2019s published examples <a href=\"https:\/\/callsphere.ai\/blog\/voicemail-detection-accuracy-callsphere-vs-vapi\" target=\"_blank\" rel=\"noindex nofollow\">use 1200 ms<\/a>. Other platforms do not publish this value.<\/p>\n<h3>Initial Silence Timeout (3000\u20135000 ms)<\/h3>\n<p>This parameter defines how long the system waits for any speech before returning an <code>unknown<\/code> result due to dead air. On Twilio, <code>MachineDetectionSilenceTimeout<\/code> defaults to 5000 ms, with a valid range of 2000\u201310000 ms. Vapi\u2019s published examples <a href=\"https:\/\/callsphere.ai\/blog\/voicemail-detection-accuracy-callsphere-vs-vapi\" target=\"_blank\" rel=\"noindex nofollow\">use 5000 ms<\/a>. Twilio recommends 3000 ms when the goal is to return <code>unknown<\/code> quickly after silent pickups. Other platforms do not publish this value.<\/p>\n<h2>How to Diagnose a Voicemail Detection Timeout That Is Too Short<\/h2>\n<p>Once the four threshold categories are clear, the next step is understanding what breaks when the overall detection timeout is set too low. A <code>MachineDetectionTimeout<\/code> set too low produces three observable failure modes.<\/p>\n<p>First, premature <code>unknown<\/code> classifications increase. Twilio\u2019s documentation confirms that a low timeout value produces more <code>unknown<\/code> AMD results because the engine stops listening before it has enough audio for a confident decision. <code>unknown<\/code> functions as a timeout signal rather than a third classification category.<\/p>\n<p>Second, when using <code>MachineDetection=DetectMessageEnd<\/code>, a short timeout breaks message-end detection. Twilio states that <code>MachineDetectionTimeout<\/code> is only relevant for <code>DetectMessageEnd<\/code>, and that a low value may return <code>unknown<\/code> even when a machine answered because the timeout fires before the greeting and beep complete.<\/p>\n<p>Third, live calls can be misrouted. <a href=\"https:\/\/allanninal.dev\/twilio\/amd-machine-answer-misrouting\" target=\"_blank\" rel=\"noindex nofollow\">A <code>machine_start<\/code> call lasting only a few seconds is the signature of a misrouted human<\/a>. A person answers, the detection classifies them as a machine, a voicemail drop starts, and the person hangs up while the call still bills as completed.<\/p>\n<h2>How to Set Twilio MachineDetectionTimeout<\/h2>\n<p>On Twilio, the parameter is <code>MachineDetectionTimeout<\/code>, expressed in seconds. The default and valid range are covered above. Values above 60 are reduced to 60, and invalid non-numeric values default to 60. The parameter is set on the outbound call create request alongside <code>machineDetection<\/code> (which accepts <code>Enable<\/code> or <code>DetectMessageEnd<\/code>), <code>MachineDetectionSpeechThreshold<\/code>, <code>MachineDetectionSpeechEndThreshold<\/code>, and <code>MachineDetectionSilenceTimeout<\/code>.<\/p>\n<p>Twilio notes that 30 seconds is sufficient for most residential voicemail boxes but frequently not enough for business voicemail boxes, and that most configuration changes observed in production are decreases rather than increases.<\/p>\n<h2>How to Configure Vapi and Retell Voicemail Detection Timeout<\/h2>\n<p><a href=\"https:\/\/callsphere.ai\/blog\/voicemail-detection-accuracy-callsphere-vs-vapi\" target=\"_blank\" rel=\"noindex nofollow\">Vapi\u2019s voicemail detection routes through Twilio AMD<\/a>. <a href=\"https:\/\/callsphere.ai\/blog\/voicemail-detection-accuracy-callsphere-vs-vapi\" target=\"_blank\" rel=\"noindex nofollow\">One published Vapi configuration example uses <code>machineDetectionTimeout: 30<\/code>, mirroring Twilio\u2019s AMD default<\/a>. The same example sets <code>machineDetectionSpeechThreshold: 2400<\/code>, <code>machineDetectionSpeechEndThreshold: 1200<\/code>, and <code>machineDetectionSilenceTimeout: 5000<\/code>. Vapi\u2019s own documented default is not confirmed. <a href=\"https:\/\/roark.ai\/blog\/testing-voicemail-detection-outbound-voice-agents\" target=\"_blank\" rel=\"noindex nofollow\">Vapi\u2019s current recommended path for voicemail detection is LLM-based detection via function calling, with the Twilio AMD path marked legacy<\/a>. Parameter names match Twilio\u2019s convention and use the same units.<\/p>\n<p>Retell does not publish AMD timeout parameter names, defaults, or ranges in its public documentation. According to third-party analysis, Retell treats voicemail and IVR detection as a first-class agent setting that runs within a timeout window. Engineers configuring Retell should consult Retell\u2019s support documentation or account team for current defaults.<\/p>\n<h2>How to Configure LiveKit and Pipecat Voicemail Detection Settings<\/h2>\n<p>LiveKit does not ship a single named voicemail detection timeout parameter equivalent to Twilio\u2019s <code>MachineDetectionTimeout<\/code>. LiveKit\u2019s AMD implementation returns one of five values: <code>human<\/code>, <code>machine-ivr<\/code>, <code>machine-vm<\/code>, <code>machine-unavailable<\/code>, or <code>uncertain<\/code>. It uses a 2.5-second human speech threshold and a 20-second timeout by default. LiveKit runs a fast heuristic path for short greetings followed by silence and falls back to a language-model classifier when a transcript requires reasoning. Configuration details beyond these defaults should be confirmed from <a href=\"https:\/\/livekit.io\" target=\"_blank\" rel=\"noindex nofollow\">LiveKit\u2019s telephony documentation at docs.livekit.io\/agents\/start\/telephony\/<\/a>.<\/p>\n<p>Pipecat is an open-source framework. <a href=\"https:\/\/pipecat.ai\" target=\"_blank\" rel=\"noindex nofollow\">Pipecat does not expose a single vendor-defined AMD timeout parameter<\/a>. Voicemail detection behavior is implemented at the pipeline and transport layer. On Pipecat, a <code>VoicemailDetector<\/code> runs a parallel pipeline with a classifier whose only job is to output <code>CONVERSATION<\/code> or <code>VOICEMAIL<\/code>, gating TTS output until the decision lands. Timeout behavior is configured as part of the pipeline logic rather than through a discrete parameter. Engineers should consult <a href=\"https:\/\/pipecat.ai\" target=\"_blank\" rel=\"noindex nofollow\">Pipecat\u2019s documentation at docs.pipecat.ai<\/a> for current pipeline configuration options.<\/p>\n<h2>How to Tell Speech Threshold and Silence Timeout Apart<\/h2>\n<p>Across these platforms, two parameters cause the most confusion because they sound similar but govern opposite phases of the call. These two parameters are frequently conflated.<\/p>\n<p><strong>Speech threshold<\/strong> (<code>MachineDetectionSpeechThreshold<\/code> on Twilio) measures the duration of continuous speech after the call connects. If speech runs longer than the threshold, the system classifies the answering party as a machine. If speech is shorter, it may classify as human. This parameter fires during active speech. As noted earlier, the default is 2400 ms on Twilio.<\/p>\n<p><strong>Initial silence timeout<\/strong> (<code>MachineDetectionSilenceTimeout<\/code> on Twilio, default 5000 ms) measures how long the system waits for any speech to begin after the call connects. If no speech appears within the silence timeout window, the system returns <code>unknown<\/code>. This parameter fires during silence before any speech starts.<\/p>\n<p>The interaction works as follows. If a call connects and the answering party says nothing for 5 seconds, the silence timeout fires and returns <code>unknown<\/code> before the speech threshold is evaluated. If the answering party speaks immediately, the silence timeout is bypassed and the speech threshold takes over. Twilio advises using <code>MachineDetectionSilenceTimeout<\/code> set to 3000 ms when the goal is to return <code>unknown<\/code> quickly after silent pickups, because the two parameters address different failure modes.<\/p>\n<h2>How to Troubleshoot Voicemail Detection Timeout Settings<\/h2>\n<p>The matrix below connects common AMD symptoms to likely root causes and the specific parameter to adjust. Use it as a quick diagnostic guide when your AMD distribution shows unexpected patterns.<\/p>\n<table>\n<thead>\n<tr>\n<th>Observed Symptom<\/th>\n<th>Root Cause<\/th>\n<th>Parameter to Change<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>High share of <code>unknown<\/code> results<\/td>\n<td>Detection timing out before verdict<\/td>\n<td>Raise <code>MachineDetectionTimeout<\/code>; raise <code>MachineDetectionSpeechThreshold<\/code><\/td>\n<\/tr>\n<tr>\n<td>Agent connects to dead air after voicemail pickup<\/td>\n<td>Timeout too short; greeting not finished before deadline<\/td>\n<td>Raise <code>MachineDetectionTimeout<\/code> to 45+ seconds for residential<\/td>\n<\/tr>\n<tr>\n<td>Voicemail message starts mid-greeting, cutting off first words<\/td>\n<td>Beep not detected before timeout; <code>DetectMessageEnd<\/code> deadline firing early<\/td>\n<td>Raise <code>MachineDetectionTimeout<\/code>; verify <code>MachineDetection=DetectMessageEnd<\/code> is set<\/td>\n<\/tr>\n<tr>\n<td>Live humans routed to voicemail drop (short <code>machine_start<\/code> calls)<\/td>\n<td>Mode problem: <code>Enable<\/code> deciding too early on borderline greetings<\/td>\n<td>Switch to <code>MachineDetection=DetectMessageEnd<\/code> or enable <code>AsyncAmd=true<\/code><\/td>\n<\/tr>\n<tr>\n<td>Calls returning <code>unknown<\/code> after silent pickup<\/td>\n<td>Initial silence exceeds silence timeout<\/td>\n<td>Lower <code>MachineDetectionSilenceTimeout<\/code> to 3000 ms to return <code>unknown<\/code> faster<\/td>\n<\/tr>\n<tr>\n<td>Short voicemail greetings classified as human<\/td>\n<td>Speech threshold too high relative to greeting length<\/td>\n<td>Lower <code>MachineDetectionSpeechThreshold<\/code> to 1500\u20132000 ms; raise <code>MachineDetectionSpeechEndThreshold<\/code> to 2000\u20132500 ms<\/td>\n<\/tr>\n<tr>\n<td>Business receptionists classified as machines<\/td>\n<td>Long human greeting exceeds speech threshold<\/td>\n<td>Raise <code>MachineDetectionSpeechThreshold<\/code> to 3000 ms for business-line campaigns<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><a href=\"https:\/\/plura.ai\/ai-predictive-dialer\" target=\"_blank\" rel=\"noindex nofollow\"><strong>Compare native detection to parameter-based AMD in a live Plura demo<\/strong><\/a>.<\/p>\n<h2>How to Keep Unit Discipline for Seconds and Milliseconds<\/h2>\n<p>The most common misconfiguration in voicemail detection is entering a value in the wrong unit. On Twilio, the four AMD parameters use two different units in the same API call. The list below shows each parameter, its unit, and its default and range.<\/p>\n<ul>\n<li><code>MachineDetectionTimeout<\/code>: <strong>seconds<\/strong> (default 30, range 3\u201359)<\/li>\n<li><code>MachineDetectionSpeechThreshold<\/code>: <strong>milliseconds<\/strong> (default 2400, range 1000\u20136000)<\/li>\n<li><code>MachineDetectionSpeechEndThreshold<\/code>: <strong>milliseconds<\/strong> (default 1200, range 500\u20135000)<\/li>\n<li><code>MachineDetectionSilenceTimeout<\/code>: <strong>milliseconds<\/strong> (default 5000, range 2000\u201310000)<\/li>\n<\/ul>\n<p>The two units create two opposite failure modes. Entering 30000 for <code>MachineDetectionTimeout<\/code> (treating it as milliseconds) will be capped at 60 seconds by Twilio, not interpreted as 30 seconds. Entering 30 for <code>MachineDetectionSpeechThreshold<\/code> (treating it as seconds) sets a 30 ms speech threshold, which will classify nearly every call as human regardless of greeting length.<\/p>\n<p>Amazon Connect\u2019s <code>RingTimeoutInSeconds<\/code> is expressed in seconds, consistent with Twilio\u2019s overall timeout convention. LiveKit\u2019s published defaults are expressed in seconds for the overall timeout and seconds for the speech threshold. Always verify the unit in the vendor\u2019s parameter reference before setting a value.<\/p>\n<h2>How to Balance Speed, Accuracy, and Cost<\/h2>\n<p>A detector tuned to be confident is a detector that is late. That tradeoff is a policy decision rather than a tuning decision. The timeout value you set determines where you land on three competing axes: detection speed, classification accuracy, and billing cost per call. The table below shows recommended timeout bands for common use cases and the rationale behind each.<\/p>\n<table>\n<thead>\n<tr>\n<th>Use Case<\/th>\n<th>Recommended Timeout Band<\/th>\n<th>Rationale<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Fast-connect AI agents (outbound lead response)<\/td>\n<td><a href=\"https:\/\/agents.bubblyphone.com\/blog\/voicemail-detection-ai-phone-agents-developer-guide\" target=\"_blank\" rel=\"noindex nofollow\">Roughly 2\u20134 seconds, with detection windows kept under about 3 seconds<\/a><\/td>\n<td>Prioritizes speed, accepts higher <code>unknown<\/code> rate, protects live-answer experience<\/td>\n<\/tr>\n<tr>\n<td>Residential voicemail outreach<\/td>\n<td>Default 30 seconds is probably sufficient for most cases<\/td>\n<td>Covers varied personal greeting lengths and reduces <code>unknown<\/code> and mid-greeting drops<\/td>\n<\/tr>\n<tr>\n<td>Business-line outreach<\/td>\n<td>10\u201315 seconds<\/td>\n<td>Business greetings tend to be brief, so shorter timeouts reduce idle billing seconds<\/td>\n<\/tr>\n<tr>\n<td>High-value lead campaigns (accuracy priority)<\/td>\n<td>20\u201330 seconds<\/td>\n<td>Accepts slower detection for 97\u201398.5% accuracy when false positives cost more than delay<sup data-disclaimer-id=\"24\" data-disclaimer-index=\"3\">3<\/sup><\/td>\n<\/tr>\n<tr>\n<td>International calling<\/td>\n<td>25\u201335 seconds<\/td>\n<td>Handles wider variation in voicemail implementations and carrier behavior across countries<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><a href=\"https:\/\/dialsheet.io\/resources\/voicemail-drops-for-cold-calling\" target=\"_blank\" rel=\"noindex nofollow\">Twilio bills $0.0075 per call for AMD on every dial it is enabled for, whether or not a machine answers<\/a><sup data-disclaimer-id=\"24\" data-disclaimer-index=\"3\">3<\/sup>. A longer timeout does not change per-call AMD cost, but it extends the window during which a connected call accrues per-minute charges. <a href=\"https:\/\/dialsheet.io\/resources\/voicemail-drops-for-cold-calling\" target=\"_blank\" rel=\"noindex nofollow\">Keeping voicemail drop clips short, around fifteen seconds per the cited source, helps keep most voicemail calls inside a single billed minute<\/a>, since carriers round each call up to the next whole minute.<\/p>\n<h2>How to Handle DetectMessageEnd and Beep Detection<\/h2>\n<p><code>MachineDetection=DetectMessageEnd<\/code> is the mode used for leaving a voicemail after the beep rather than mid-greeting. It waits for the machine greeting to finish before returning a verdict. The possible return values are <code>machine_end_beep<\/code>, <code>machine_end_silence<\/code>, <code>machine_end_other<\/code>, <code>human<\/code>, <code>fax<\/code>, and <code>unknown<\/code>.<\/p>\n<p>A short <code>MachineDetectionTimeout<\/code> breaks this mode directly. Twilio states that when <code>MachineDetection=DetectMessageEnd<\/code>, low values for <code>MachineDetectionTimeout<\/code> may return <code>unknown<\/code> even if a machine answered and the engine could have determined so, because the timeout triggers before the end of the machine greeting. In that case, Twilio may return <code>machine_end_other<\/code> as the fallback.<\/p>\n<p>Twilio notes that 30 seconds is frequently not enough for business voicemail boxes when using <code>DetectMessageEnd<\/code>. For campaigns targeting business lines with long greetings, Twilio documents increasing <code>MachineDetectionTimeout<\/code> within its allowed range as the remedy.<\/p>\n<h2>How to Adjust for iOS 26 Call Screening<\/h2>\n<p>iOS 26 introduced expanded call screening that intercepts calls from unfamiliar numbers before they ring through to the recipient. <a href=\"https:\/\/roark.ai\/blog\/testing-voicemail-detection-outbound-voice-agents\" target=\"_blank\" rel=\"noindex nofollow\">A LiveKit Agents user running thousands of answered calls per day reports that around 30% of their calls are voicemail or iOS 26 Call Screening bots<\/a><sup data-disclaimer-id=\"24\" data-disclaimer-index=\"3\">3<\/sup>, and that share has been climbing as more recipients turn screening on.<\/p>\n<p>iOS 26 screening creates a new AMD edge case. The call is answered by a screening bot rather than a human or a carrier voicemail system. The screening bot may ask the caller to state their name or reason for calling before deciding whether to pass the call through. This interactive automated response does not match the audio patterns of either a standard human greeting or a carrier voicemail greeting, so standard AMD thresholds tuned for those two cases may misclassify screened calls.<\/p>\n<p>The practical effect on timeout settings is straightforward. Screened calls may produce longer initial audio than a human greeting but shorter than a full voicemail greeting, landing in the ambiguous zone around the speech threshold. Increasing <code>MachineDetectionSpeechThreshold<\/code> toward 3000 ms and using <code>DetectMessageEnd<\/code> rather than <code>Enable<\/code> reduces the risk of classifying a screening interaction as a live human pickup. Platforms that communicate with iOS 26\u2019s call-screening layer at the carrier level can present a recognizable caller identity to the screening system, which converts screened calls into pickups before AMD runs.<\/p>\n<h2>How Plura AI Handles Voicemail Detection Timeout Settings<\/h2>\n<p>All of the platform-specific configuration above assumes you are managing AMD through third-party APIs. Plura AI takes a different approach. Plura\u2019s <a href=\"https:\/\/plura.ai\/ai-predictive-dialer\" target=\"_blank\" rel=\"noindex nofollow\">AI Predictive Dialer<\/a> runs <a href=\"https:\/\/plura.ai\/ai-predictive-dialer\" target=\"_blank\" rel=\"noindex nofollow\">voicemail detection<\/a> natively on Plura\u2019s own FCC-licensed audio bridging carrier, not through a third-party CPaaS. This architectural difference affects timeout configuration. Because Plura owns the carrier layer, detection, branded caller ID issuance, and real-time DNC (Do Not Call) scrubbing are enforced inside the platform before dial. This differs from API-wrapper tools, where these functions are bolted on through parameters passed to a third-party network.<\/p>\n<p>For operations teams currently managing <code>MachineDetectionTimeout<\/code>, <code>MachineDetectionSpeechThreshold<\/code>, and related parameters across Twilio-based API resellers, Plura\u2019s native detection layer reduces the parameter-guessing those tools require. The platform handles the detection decision internally, and timeout behavior is managed at the carrier level rather than through per-call API configuration.<\/p>\n<p>Plura\u2019s AI Predictive Dialer is a <a href=\"https:\/\/plura.ai\/ai-predictive-dialer\" target=\"_blank\" rel=\"noindex nofollow\">Vici Dial alternative<\/a> and supports <a href=\"https:\/\/plura.ai\/ai-predictive-dialer\" target=\"_blank\" rel=\"noindex nofollow\">multi-line dialing<\/a>. It shares a Stateful Conversation Database with Plura\u2019s AI SMS, AI RCS, and AI Webchat channels, so context from a prior text or web interaction is available to the dialer on the next outbound call. STIR\/SHAKEN (Secure Telephone Identity Revisited \/ Signature-based Handling of Asserted information using toKENs) caller ID authentication runs on every outbound call.<sup data-disclaimer-id=\"22\" data-disclaimer-index=\"1\">1<\/sup> Plura supports TCPA (Telephone Consumer Protection Act) and DNC compliance workflows at the platform level on every outbound contact.<sup data-disclaimer-ids=\"22,23\" data-disclaimer-indexes=\"1,2\">1,2<\/sup> Customers remain responsible for their own compliance obligations and should consult qualified counsel regarding their specific regulatory requirements.<\/p>\n<p><a href=\"https:\/\/plura.ai\/ai-predictive-dialer\" target=\"_blank\" rel=\"noindex nofollow\"><strong>Watch a live demo of carrier-level detection with Plura<\/strong><\/a>.<\/p>\n<h2>Frequently Asked Questions (FAQ)<\/h2>\n<h3>What Happens If the Voicemail Detection Timeout Is Too Short?<\/h3>\n<p>A timeout set too low produces the three failure modes described earlier: more <code>unknown<\/code> results, broken message-end detection, and misrouted live calls. The observable symptom of the third failure is a cluster of very short <code>machine_start<\/code> calls in your AMD distribution.<\/p>\n<h3>Does DetectMessageEnd Change the Timeout?<\/h3>\n<p>DetectMessageEnd does not change the numeric value of <code>MachineDetectionTimeout<\/code>, but it changes what that timeout governs. In <code>Enable<\/code> mode, the timeout bounds how long the engine waits to make any human, machine, or <code>unknown<\/code> decision. In DetectMessageEnd mode, the timeout bounds how long the engine waits for the greeting to finish before it can return a <code>machine_end_beep<\/code>, <code>machine_end_silence<\/code>, or <code>machine_end_other<\/code> verdict. Because DetectMessageEnd must wait for the entire greeting to complete, the same 30-second default that is sufficient in <code>Enable<\/code> mode is frequently insufficient for business voicemail boxes with long greetings. Twilio\u2019s documentation notes that almost all configuration changes observed in production are decreases rather than increases.<\/p>\n<h3>What Is the Difference Between Speech Threshold and Silence Timeout?<\/h3>\n<p>Speech threshold (<code>MachineDetectionSpeechThreshold<\/code> on Twilio) measures the duration of continuous speech after the call connects. If speech runs longer than the threshold, the system classifies the answering party as a machine. If speech is shorter, it may classify as human. This parameter fires during active speech.<\/p>\n<hr data-disclaimer-divider=\"true\">\n<div data-disclaimer-footer=\"true\">\n<p data-disclaimer-id=\"22\" data-disclaimer-type=\"content_based\"><sup data-disclaimer-index=\"1\">1<\/sup> Plura AI maintains SOC 2, HIPAA, ISO, and GDPR posture as part of its platform infrastructure. References to compliance frameworks in this article describe Plura\u2019s platform capabilities and do not constitute a guarantee that any customer using Plura will themselves be compliant with applicable laws or standards. Customers remain solely responsible for their own regulatory obligations, certifications, consent management, recordkeeping, and the claims they make to their own end users. Consult qualified legal counsel for guidance specific to your use case.<\/p>\n<p data-disclaimer-id=\"23\" data-disclaimer-type=\"content_based\"><sup data-disclaimer-index=\"2\">2<\/sup> This article describes regulatory frameworks at a general level and does not constitute legal advice. Laws and regulations vary by jurisdiction, change over time, and apply differently depending on facts and circumstances. Readers should consult qualified legal counsel before making compliance decisions.<\/p>\n<p data-disclaimer-id=\"24\" data-disclaimer-type=\"content_based\"><sup data-disclaimer-index=\"3\">3<\/sup> Performance figures, customer outcomes, and industry statistics referenced in this article are drawn from cited third-party sources or Plura customer case studies. Individual results vary based on implementation, use case, industry, audience, and execution. Past or aggregate performance is not a guarantee of future results.<\/p>\n<p data-disclaimer-id=\"25\" data-disclaimer-type=\"content_based\"><sup data-disclaimer-index=\"4\">4<\/sup> References to third-party products, services, companies, or research are made for informational and comparative purposes only. Plura AI is not affiliated with, endorsed by, or sponsored by any third party named in this article unless explicitly stated. Trademarks and product names referenced remain the property of their respective owners.<\/p>\n<p data-disclaimer-id=\"21\" data-disclaimer-type=\"fixed\">This article is provided for informational purposes only and reflects Plura AI\u2019s understanding at the time of publication. Product capabilities, integrations, and specifications are subject to change. For the most current information, visit plura.ai.<\/p>\n<p data-disclaimer-id=\"27\" data-disclaimer-type=\"fixed\">This article was produced with the assistance of AI tools and reviewed by Plura AI prior to publication.<\/p>\n<\/div>\n<section data-read-next=\"true\">\n<h2>Read Next<\/h2>\n<ul>\n<li><a href=\"https:\/\/www.plura.ai\/articles\/voicemail-detection-parameters\" target=\"_blank\">Voicemail Detection Parameters: Cross-Platform Guide<\/a><\/li>\n<li><a href=\"https:\/\/www.plura.ai\/articles\/how-vapi-handles-voicemail-detection\" target=\"_blank\">How Vapi Handles Voicemail Detection: A Configuration Guide<\/a><\/li>\n<li><a href=\"https:\/\/www.plura.ai\/articles\/voicemail-drop-after-detection\" target=\"_blank\">Voicemail Drop After Detection: The 2026 Setup Guide<\/a><\/li>\n<li><a href=\"https:\/\/www.plura.ai\/articles\/improve-voicemail-detection-accuracy\" target=\"_blank\">How to Improve Voicemail Detection Accuracy: 2026 Guide<\/a><\/li>\n<li><a href=\"https:\/\/www.plura.ai\/articles\/voicemail-detection-integration\" target=\"_blank\">Voicemail Detection Integration for Contact Centers<\/a><\/li>\n<\/ul>\n<\/section>\n","protected":false},"excerpt":{"rendered":"<p>Configure voicemail detection timeout settings across Twilio, Vapi, Retell, and more. Plura AI gives contact center leaders smarter call intelligence.<\/p>\n","protected":false},"author":106,"featured_media":3549,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[8],"tags":[],"class_list":["post-3550","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-voice-agents"],"_links":{"self":[{"href":"https:\/\/www.plura.ai\/articles\/wp-json\/wp\/v2\/posts\/3550","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.plura.ai\/articles\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.plura.ai\/articles\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/www.plura.ai\/articles\/wp-json\/wp\/v2\/comments?post=3550"}],"version-history":[{"count":1,"href":"https:\/\/www.plura.ai\/articles\/wp-json\/wp\/v2\/posts\/3550\/revisions"}],"predecessor-version":[{"id":3554,"href":"https:\/\/www.plura.ai\/articles\/wp-json\/wp\/v2\/posts\/3550\/revisions\/3554"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.plura.ai\/articles\/wp-json\/wp\/v2\/media\/3549"}],"wp:attachment":[{"href":"https:\/\/www.plura.ai\/articles\/wp-json\/wp\/v2\/media?parent=3550"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.plura.ai\/articles\/wp-json\/wp\/v2\/categories?post=3550"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.plura.ai\/articles\/wp-json\/wp\/v2\/tags?post=3550"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}