> ## Documentation Index
> Fetch the complete documentation index at: https://docs.galileo.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Interruption Detection

> Detect turn-taking violations in audio-based agent conversations, including agent overlap, premature agent barge-in, and user barge-in

export const BooleanClassificationReport = ({report, negativeLabel = "Not Advanced", positiveLabel = "Advanced", negativeClass = "False", positiveClass = "True", maxWidth = 520}) => {
  const parseReport = reportStr => {
    const lines = reportStr.trim().split('\n').filter(line => line.trim());
    const result = {
      classes: [],
      accuracy: null,
      macroAvg: null,
      weightedAvg: null,
      totalSupport: null
    };
    for (const line of lines) {
      const parts = line.trim().split(/\s+/);
      if (parts[0] === 'precision') continue;
      if (parts.length >= 5 && !['accuracy', 'macro', 'weighted'].includes(parts[0])) {
        result.classes.push({
          name: parts[0],
          precision: parseFloat(parts[1]),
          recall: parseFloat(parts[2]),
          f1: parseFloat(parts[3]),
          support: parseInt(parts[4], 10)
        });
      }
      if (parts[0] === 'accuracy') {
        result.accuracy = parseFloat(parts[1]);
        result.totalSupport = parseInt(parts[2], 10);
      }
      if (parts[0] === 'macro' && parts[1] === 'avg') {
        result.macroAvg = {
          precision: parseFloat(parts[2]),
          recall: parseFloat(parts[3]),
          f1: parseFloat(parts[4]),
          support: parseInt(parts[5], 10)
        };
      }
      if (parts[0] === 'weighted' && parts[1] === 'avg') {
        result.weightedAvg = {
          precision: parseFloat(parts[2]),
          recall: parseFloat(parts[3]),
          f1: parseFloat(parts[4]),
          support: parseInt(parts[5], 10)
        };
      }
    }
    return result;
  };
  const parsed = parseReport(report);
  if (parsed.classes.length < 2) {
    return <div style={{
      color: "red",
      padding: "1rem",
      border: "1px solid red"
    }}>BooleanClassificationReport: Could not parse report. Expected at least 2 classes.</div>;
  }
  const negClass = parsed.classes.find(c => c.name === negativeClass) || parsed.classes[0];
  const posClass = parsed.classes.find(c => c.name === positiveClass) || parsed.classes[1];
  const tnPlusFp = negClass.support;
  const tpPlusFn = posClass.support;
  const tn = Math.round(negClass.recall * tnPlusFp);
  const fp = tnPlusFp - tn;
  const tp = Math.round(posClass.recall * tpPlusFn);
  const fn = tpPlusFn - tp;
  const tnPct = tn / tnPlusFp * 100;
  const fpPct = fp / tnPlusFp * 100;
  const fnPct = fn / tpPlusFn * 100;
  const tpPct = tp / tpPlusFn * 100;
  const rowStyle = {
    borderBottom: "1px solid rgba(148, 163, 184, 0.3)"
  };
  const cellStyle = {
    padding: "0.5rem 0.125rem"
  };
  const centerCellStyle = {
    textAlign: "center",
    padding: "0.5rem 0.125rem"
  };
  return <div>
      {}
      <table style={{
    width: "auto",
    borderCollapse: "collapse",
    marginBottom: "1.5rem",
    fontSize: "0.875rem"
  }}>
        <thead>
          <tr style={{
    borderBottom: "2px solid rgba(148, 163, 184, 0.5)"
  }}>
            <th style={{
    textAlign: "center",
    padding: "0.5rem 0.125rem",
    fontWeight: "600"
  }}></th>
            <th style={{
    textAlign: "center",
    padding: "0.5rem 0.125rem",
    fontWeight: "600"
  }}>Precision</th>
            <th style={{
    textAlign: "center",
    padding: "0.5rem 0.125rem",
    fontWeight: "600"
  }}>Recall</th>
            <th style={{
    textAlign: "center",
    padding: "0.5rem 0.125rem",
    fontWeight: "600"
  }}>F1-Score</th>
          </tr>
        </thead>
        <tbody>
          {}
          <tr style={rowStyle}>
            <td style={cellStyle}>{negativeLabel}</td>
            <td style={centerCellStyle}>{negClass.precision.toFixed(2)}</td>
            <td style={centerCellStyle}>{negClass.recall.toFixed(2)}</td>
            <td style={centerCellStyle}>{negClass.f1.toFixed(2)}</td>
          </tr>
          <tr style={rowStyle}>
            <td style={cellStyle}>{positiveLabel}</td>
            <td style={centerCellStyle}>{posClass.precision.toFixed(2)}</td>
            <td style={centerCellStyle}>{posClass.recall.toFixed(2)}</td>
            <td style={centerCellStyle}>{posClass.f1.toFixed(2)}</td>
          </tr>
          
        </tbody>
      </table>

      {}
      <BooleanConfusionMatrix actualNegativeLabel={negativeLabel} actualPositiveLabel={positiveLabel} predictedNegativeLabel={negativeLabel} predictedPositiveLabel={positiveLabel} tnPct={tnPct.toString()} fpPct={fpPct.toString()} fnPct={fnPct.toString()} tpPct={tpPct.toString()} displayFormat="fraction" maxWidth={maxWidth} />
    </div>;
};

export const BooleanConfusionMatrix = ({actualNegativeLabel = "Not Advanced", actualPositiveLabel = "Advanced", predictedNegativeLabel = "Not Advanced", predictedPositiveLabel = "Advanced", tnCount, tnPct, fpCount, fpPct, fnCount, fnPct, tpCount, tpPct, matrix, maxWidth = 520, displayFormat = "percentage", fractionDigits = 3, percentageDigits = 1, titlePrefix = ""}) => {
  const parseNum = val => val !== undefined && val !== null ? Number(val) : undefined;
  const clampPct = pct => Math.max(0, Math.min(100, Number(pct) || 0));
  const formatValue = pct => {
    const p = clampPct(pct);
    if (displayFormat === "fraction") {
      const digits = Number.isFinite(Number(fractionDigits)) ? Number(fractionDigits) : 3;
      return (p / 100).toFixed(digits);
    }
    const digits = Number.isFinite(Number(percentageDigits)) ? Number(percentageDigits) : 1;
    return `${p.toFixed(digits)}%`;
  };
  const palette = ["#f8fafc", "#eff6ff", "#dbeafe", "#bfdbfe", "#93c5fd", "#60a5fa", "#3b82f6", "#2563eb", "#1d4ed8", "#1e40af"];
  const getBg = pct => {
    const p = clampPct(pct);
    const idx = p === 100 ? 9 : Math.floor(p / 10);
    return palette[idx];
  };
  const getColor = pct => clampPct(pct) >= 60 ? "#ffffff" : "#1e3a8a";
  const rawTn = parseNum(tnCount);
  const rawFp = parseNum(fpCount);
  const rawFn = parseNum(fnCount);
  const rawTp = parseNum(tpCount);
  const rawTnPct = parseNum(tnPct);
  const rawFpPct = parseNum(fpPct);
  const rawFnPct = parseNum(fnPct);
  const rawTpPct = parseNum(tpPct);
  const hasCounts = rawTn !== undefined && rawFp !== undefined && rawFn !== undefined && rawTp !== undefined;
  const hasPcts = rawTnPct !== undefined && rawFpPct !== undefined && rawFnPct !== undefined && rawTpPct !== undefined;
  let resolvedMatrix;
  let showCounts;
  if (matrix) {
    resolvedMatrix = matrix;
    showCounts = matrix.tn?.count !== undefined;
  } else if (hasCounts) {
    const actualNegTotal = rawTn + rawFp;
    const actualPosTotal = rawFn + rawTp;
    resolvedMatrix = {
      tn: {
        count: rawTn,
        pct: actualNegTotal > 0 ? rawTn / actualNegTotal * 100 : 0
      },
      fp: {
        count: rawFp,
        pct: actualNegTotal > 0 ? rawFp / actualNegTotal * 100 : 0
      },
      fn: {
        count: rawFn,
        pct: actualPosTotal > 0 ? rawFn / actualPosTotal * 100 : 0
      },
      tp: {
        count: rawTp,
        pct: actualPosTotal > 0 ? rawTp / actualPosTotal * 100 : 0
      }
    };
    showCounts = true;
  } else if (hasPcts) {
    resolvedMatrix = {
      tn: {
        pct: rawTnPct
      },
      fp: {
        pct: rawFpPct
      },
      fn: {
        pct: rawFnPct
      },
      tp: {
        pct: rawTpPct
      }
    };
    showCounts = false;
  } else {
    return <div style={{
      color: "red",
      padding: "1rem",
      border: "1px solid red"
    }}>BooleanConfusionMatrix: Provide either all counts or all percentages</div>;
  }
  const cellStyle = pct => ({
    background: getBg(pct),
    color: getColor(pct),
    padding: "1rem",
    textAlign: "center",
    borderRadius: "8px",
    aspectRatio: "1 / 1",
    width: "100%",
    display: "flex",
    flexDirection: "column",
    alignItems: "center",
    justifyContent: "center",
    border: "1px solid rgba(148, 163, 184, 0.35)"
  });
  const displayPredictedLabels = {
    left: predictedPositiveLabel,
    right: predictedNegativeLabel
  };
  const displayActualLabels = {
    top: actualPositiveLabel,
    bottom: actualNegativeLabel
  };
  const displayMatrix = {
    tl: resolvedMatrix.tp,
    tr: resolvedMatrix.fn,
    bl: resolvedMatrix.fp,
    br: resolvedMatrix.tn
  };
  return <div style={{
    maxWidth: maxWidth + "px",
    margin: "1rem 0"
  }}>
      <div style={{
    display: "grid",
    gridTemplateColumns: "auto auto 1fr 1fr",
    gridTemplateRows: "auto auto auto 1fr 1fr auto",
    gap: "2px"
  }}>
        {}
        <div></div>
        <div></div>
        <div style={{
    gridColumn: "3 / 5",
    textAlign: "center",
    padding: "0.5rem",
    fontWeight: "600",
    fontSize: "1rem"
  }}>
          {titlePrefix}Confusion Matrix (Normalized)
        </div>

        {}
        <div></div>
        <div></div>
        <div style={{
    gridColumn: "3 / 5",
    textAlign: "center",
    padding: "0.5rem",
    fontWeight: "600",
    fontSize: "0.875rem"
  }}>
          Predicted
        </div>

        {}
        <div></div>
        <div></div>
        <div style={{
    textAlign: "center",
    padding: "0.5rem",
    fontSize: "0.75rem",
    fontWeight: "500",
    display: "flex",
    alignItems: "center",
    justifyContent: "center"
  }}>{displayPredictedLabels.left}</div>
        <div style={{
    textAlign: "center",
    padding: "0.5rem",
    fontSize: "0.75rem",
    fontWeight: "500",
    display: "flex",
    alignItems: "center",
    justifyContent: "center"
  }}>{displayPredictedLabels.right}</div>

        {}
        <div style={{
    gridRow: "4 / 6",
    writingMode: "vertical-rl",
    transform: "rotate(180deg)",
    textAlign: "center",
    fontWeight: "600",
    fontSize: "0.875rem",
    padding: "0 0.5rem",
    display: "flex",
    alignItems: "center",
    justifyContent: "center"
  }}>
          Actual
        </div>
        <div style={{
    padding: "0.5rem",
    fontSize: "0.75rem",
    fontWeight: "500",
    display: "flex",
    alignItems: "center",
    justifyContent: "flex-end"
  }}>{displayActualLabels.top}</div>
        <div style={cellStyle(displayMatrix.tl.pct)}>
          {showCounts && <div style={{
    fontSize: "1.5rem",
    fontWeight: "700",
    lineHeight: 1
  }}>{displayMatrix.tl.count}</div>}
          <div style={{
    fontSize: showCounts ? "0.75rem" : "1rem",
    fontWeight: showCounts ? "400" : "700",
    opacity: showCounts ? 0.8 : 1
  }}>{formatValue(displayMatrix.tl.pct)}</div>
        </div>
        <div style={cellStyle(displayMatrix.tr.pct)}>
          {showCounts && <div style={{
    fontSize: "1.5rem",
    fontWeight: "700",
    lineHeight: 1
  }}>{displayMatrix.tr.count}</div>}
          <div style={{
    fontSize: showCounts ? "0.75rem" : "1rem",
    fontWeight: showCounts ? "400" : "700",
    opacity: showCounts ? 0.8 : 1
  }}>{formatValue(displayMatrix.tr.pct)}</div>
        </div>

        {}
        <div style={{
    padding: "0.5rem",
    fontSize: "0.75rem",
    fontWeight: "500",
    display: "flex",
    alignItems: "center",
    justifyContent: "flex-end"
  }}>{displayActualLabels.bottom}</div>
        <div style={cellStyle(displayMatrix.bl.pct)}>
          {showCounts && <div style={{
    fontSize: "1.5rem",
    fontWeight: "700",
    lineHeight: 1
  }}>{displayMatrix.bl.count}</div>}
          <div style={{
    fontSize: showCounts ? "0.75rem" : "1rem",
    fontWeight: showCounts ? "400" : "700",
    opacity: showCounts ? 0.8 : 1
  }}>{formatValue(displayMatrix.bl.pct)}</div>
        </div>
        <div style={cellStyle(displayMatrix.br.pct)}>
          {showCounts && <div style={{
    fontSize: "1.5rem",
    fontWeight: "700",
    lineHeight: 1
  }}>{displayMatrix.br.count}</div>}
          <div style={{
    fontSize: showCounts ? "0.75rem" : "1rem",
    fontWeight: showCounts ? "400" : "700",
    opacity: showCounts ? 0.8 : 1
  }}>{formatValue(displayMatrix.br.pct)}</div>
        </div>

        {}
        <div></div>
        <div></div>
        <div style={{
    gridColumn: "3 / 5",
    marginTop: "0.5rem",
    display: "flex",
    alignItems: "center",
    gap: "0.5rem"
  }}>
          <span style={{
    fontSize: "0.75rem",
    fontWeight: "500"
  }}>{displayFormat === "fraction" ? "0.0" : "0%"}</span>
          <div style={{
    display: "flex",
    flex: 1,
    height: "12px",
    borderRadius: "4px",
    overflow: "hidden",
    border: "1px solid rgba(148, 163, 184, 0.35)"
  }}>
            {palette.map((color, idx) => <div key={idx} style={{
    flex: 1,
    height: "100%",
    background: color
  }} />)}
          </div>
          <span style={{
    fontSize: "0.75rem",
    fontWeight: "500"
  }}>{displayFormat === "fraction" ? "1.0" : "100%"}</span>
        </div>
      </div>
    </div>;
};

export const MetricWhenToUse = ({description, useCases}) => {
  return <Card>
      <div style={{
    display: 'flex',
    alignItems: 'center',
    gap: '0.5rem',
    marginBottom: '0.75rem'
  }}>
        <div style={{
    fontSize: '1.25rem',
    color: 'var(--primary-color)'
  }}>
          <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2" strokeLinecap="round" strokeLinejoin="round">
            <path d="M12 22c5.523 0 10-4.477 10-10S17.523 2 12 2 2 6.477 2 12s4.477 10 10 10z" />
            <path d="m9 12 2 2 4-4" />
          </svg>
        </div>
        <h3 style={{
    margin: 0,
    fontSize: '1.25rem',
    fontWeight: '600'
  }}>When to Use This Metric</h3>
      </div>

      {description}

      {useCases != null && useCases.map((useCase, index) => <div key={index} style={{
    marginTop: "1rem",
    paddingTop: "0.75rem",
    borderTop: "1px solid rgba(209, 213, 219, 0.33)"
  }}>
          <strong>{useCase.title}</strong>{useCase.description ? `: ${useCase.description}` : ''}
        </div>)}
    </Card>;
};

export const DefinitionCard = ({children}) => {
  return <Card variant="secondary">
    <div style={{
    padding: '0.5rem',
    border: '5px solid var(--primary-light)',
    borderRadius: '0.5rem',
    fontSize: '1.3rem',
    lineHeight: '1.4',
    boxShadow: '0 0 10px 10px var(--primary-light)'
  }}>
        {children}
      </div>

</Card>;
};

export const Pill = ({label, color, backgroundColor}) => <span style={{
  display: "inline-block",
  backgroundColor: backgroundColor ?? "#C0C0C0",
  color: color ?? "#333",
  padding: "2px 8px",
  borderRadius: "12px",
  fontSize: "12px",
  fontWeight: "500",
  lineHeight: "1"
}}>
    {label}
  </span>;

<DefinitionCard>
  <strong>Interruption Detection</strong> is a session-level binary metric that identifies turn-taking violations in audio-based agent conversations — including the agent speaking over the user, the agent cutting off the user before intent
  is complete, and the user cutting off the agent.
</DefinitionCard>

Interruption Detection evaluates the full list of trace inputs and outputs in a session to determine whether any turn-taking violations occurred. It covers three interruption patterns:

* **Agent overlap**: The agent speaks while the user is still speaking
* **Premature agent barge-in**: The agent begins its response before the user's intent is complete
* **User barge-in**: The user speaks while the agent is still speaking

## Interruption Detection at a glance

| Property                       | Description                                   |
| :----------------------------- | :-------------------------------------------- |
| **Name**                       | Interruption Detection                        |
| **Category**                   | Multimodal Quality                            |
| **Metric Level**               | Session (List of trace inputs / outputs only) |
| **LLM-as-a-judge Support**     | ✅                                             |
| **Luna Support**               | ❌                                             |
| **Protect Runtime Protection** | ❌                                             |
| **Value Type**                 | Boolean                                       |

## Score interpretation

| Score     | Label                 | Meaning                                                        |
| :-------- | :-------------------- | :------------------------------------------------------------- |
| **False** | No Interruption       | No turn-taking violations were detected in the session         |
| **True**  | Interruption Detected | At least one turn-taking violation was detected in the session |

Use this score as a single session-level signal:

* <Pill label="False" /> means no overlap or barge-in was detected.
* <Pill label="True" /> means at least one interruption event occurred (agent overlap, premature agent barge-in, or user barge-in).

## When to use this metric

<MetricWhenToUse
  description="Interruption Detection is useful for audio-based conversational AI systems where smooth turn-taking is critical to user experience"
  useCases={[
{
  title: "Voice assistant and IVR quality monitoring",
  description: "Detect sessions where the agent spoke over callers or cut them off, which degrades satisfaction in customer-facing voice applications.",
},
{
  title: "Real-time audio agent evaluation",
  description: "Monitor live or recorded conversations to surface systematic turn-taking problems caused by VAD (voice activity detection) or endpoint misconfiguration.",
},
{
  title: "Conversational UX regression testing",
  description: "Catch regressions in turn-taking behavior when updating agent models, endpoint thresholds, or audio processing pipelines.",
},
{
  title: "User frustration signal",
  description: "Use user barge-in events as a proxy for user frustration or overly long agent responses.",
},
]}
/>

## Example scenario

<Card>
  <div style={{display: 'flex', alignItems: 'center', gap: '0.5rem', marginBottom: '0.75rem'}}>
    <div style={{fontSize: '1.25rem', color: 'var(--primary-color)'}}>
      <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2" strokeLinecap="round" strokeLinejoin="round">
        <path d="M12 22c5.523 0 10-4.477 10-10S17.523 2 12 2 2 6.477 2 12s4.477 10 10 10z" />

        <path d="m9 12 2 2 4-4" />
      </svg>
    </div>

    <h3 style={{margin: 0, fontSize: '1.25rem', fontWeight: '600'}}>endpoint too aggressive</h3>
  </div>

  <div style={{ marginTop: "1rem", paddingTop: "0.75rem", borderTop: "1px solid rgba(209, 213, 219, 0.33)" }}>
    <strong>User:</strong> “I need help booking a flight to—”
  </div>

  <div style={{ marginTop: "0.75rem", paddingTop: "0.75rem", borderTop: "1px solid rgba(209, 213, 219, 0.33)" }}>
    <strong>Agent:</strong> “Sure, what dates are you traveling?”
  </div>

  <div style={{ marginTop: "1rem", paddingTop: "0.75rem", borderTop: "1px solid rgba(209, 213, 219, 0.33)" }}>
    <strong>Interpretation:</strong> The agent started speaking before the user completed their intent, so the session should be labeled <Pill label="Interruption Detected" />.
  </div>
</Card>

## Interruption patterns

<Card>
  <div style={{display: 'flex', alignItems: 'center', gap: '0.5rem', marginBottom: '0.75rem'}}>
    <div style={{fontSize: '1.25rem', color: 'var(--primary-color)'}}>
      <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2" strokeLinecap="round" strokeLinejoin="round">
        <path d="M12 22c5.523 0 10-4.477 10-10S17.523 2 12 2 2 6.477 2 12s4.477 10 10 10z" />

        <path d="m9 12 2 2 4-4" />
      </svg>
    </div>

    <h3 style={{margin: 0, fontSize: '1.25rem', fontWeight: '600'}}>Types of Interruptions</h3>
  </div>

  <div style={{ marginTop: "1rem", paddingTop: "0.75rem", borderTop: "1px solid rgba(209, 213, 219, 0.33)" }}>
    <strong>Agent overlap:</strong> The agent begins or continues speaking while the user is still speaking, causing simultaneous audio output from both parties.
  </div>

  <div style={{ marginTop: "0.75rem", paddingTop: "0.75rem", borderTop: "1px solid rgba(209, 213, 219, 0.33)" }}>
    <strong>Premature agent barge-in:</strong> The agent starts its response before the user has finished expressing their intent, truncating incomplete utterances.
  </div>

  <div style={{ marginTop: "0.75rem", paddingTop: "0.75rem", borderTop: "1px solid rgba(209, 213, 219, 0.33)" }}>
    <strong>User barge-in:</strong> The user speaks while the agent is still delivering its response, often indicating frustration or an overly long agent turn.
  </div>
</Card>

## Inputs considered

Interruption Detection operates at the **session level** and is computed over the full list of trace inputs and outputs for that session. The evaluator examines:

* The ordered sequence of speaker turns (agent and user) across all traces in the session
* Audio files of the user and assistant turns

<Note>Accuracy improves when trace inputs and outputs inlcude the user / assistant audio files alongside the transcripts.</Note>

## Calculation method

Interruption Detection is computed through a multi-step process:

<Steps>
  <Step title="Session aggregation">Aggregate the full list of trace inputs and outputs for a session and identify speaker turns (user vs. agent).</Step>

  <Step title="Overlap and barge-in detection">
    Detect whether the agent speaks while the user is speaking, the agent begins responding before user intent completes, or the user speaks while the agent is speaking. Where available, use timing/overlap metadata to confirm simultaneous
    speech.
  </Step>

  <Step title="Binary decision">
    Return <Pill label="True" /> if any interruption event occurs in the session; otherwise return <Pill label="False" />.
  </Step>
</Steps>

<Note>This metric is typically computed by prompting an LLM over the session trace (and any available timing metadata), which may require additional LLM calls to compute and can impact usage and billing.</Note>

## Best practices

<CardGroup cols={2}>
  <Card title="Keep the trace inputs and outputs clean" icon="clock">
    Ensure only the latest user query is the trace input (free of chat history), and the last LLM span's output as the trace output
  </Card>

  <Card title="Include transcripts" icon="user-tag">
    Add the test versions of the trace inputs and outputs alongside the audio files.
  </Card>
</CardGroup>

## Performance Benchmarks

We evaluated Interruption Detection against human expert labels on an internal dataset of varied samples using top frontier models.

| Model          | F1 (True) |
| :------------- | :-------: |
| GPT-audio      |    0.69   |
| Gemini 3 Flash |    0.93   |
| Gemini 3 Pro   |    0.94   |

### Gemini 3 Flash Classification Report

<BooleanClassificationReport
  report={`            precision    recall  f1-score   support

False 0.93 0.94 0.94 651
True 0.93 0.91 0.92 546

accuracy 0.93 1197
macro avg 0.93 0.93 0.93 1197
weighted avg 0.93 0.93 0.93 1197`}
  negativeLabel="No Interruption"
  positiveLabel="Interruption Detected"
  negativeClass="False"
  positiveClass="True"
/>

## Related Resources

If you would like to dive deeper or start implementing Interruption Detection, check out the following resources:

### Examples

* [Interruption Detection Examples](https://app.galileo.ai) - Log in and explore the "Interruption Detection" Log Stream in the "Preset Metric Examples" Project to see this metric in action.

### Related Concepts

* [Visual Quality](/concepts/metrics/multimodal-quality/visual-quality)
* [Visual Fidelity](/concepts/metrics/multimodal-quality/visual-fidelity)
* [Conversation Quality](/concepts/metrics/agentic/conversation-quality)