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<section class="comparison-chart" aria-labelledby="comparison-chart-title">
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<div class="comparison-chart-heading">
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<div>
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<h2 id="comparison-chart-title">Model comparison</h2>
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<p>Compare model error rates for one dataset and metric. Lower is better.</p>
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</div>
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<div class="comparison-chart-controls" aria-label="Model comparison filters">
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<label>
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<span>Dataset</span>
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<select id="chart-dataset" aria-label="Chart dataset"></select>
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<label>
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<span>Metric</span>
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<select id="chart-metric" aria-label="Chart metric"></select>
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<label>
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<span>Availability</span>
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<select id="chart-availability" aria-label="Chart model availability">
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<option value="All">All models</option>
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<option value="Open">Open only</option>
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<option value="Closed">Closed only</option>
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</select>
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</div>
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</div>
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<div class="comparison-chart-card">
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<div class="comparison-bars" id="comparison-bars" aria-live="polite"></div>
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<p class="comparison-chart-empty" id="comparison-chart-empty" hidden>No models match the current filters.</p>
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</div>
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</section>
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<section class="citation-card" aria-labelledby="citation-title">
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<p class="citation-label" id="citation-title">Cite ArmBench-ASR</p>
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<p>If you use ArmBench-ASR in your research, please cite it as follows:</p>
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<pre><code>@misc{armbench-asr,
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title={ArmBench-ASR: Benchmarking Speech-to-Text Models on Armenian Speech Recognition Tasks},
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author={Metric-AI-Lab},
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year={2026},
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howpublished={\url{https://huggingface.co/spaces/Metric-AI/ArmBench-ASR}},
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note={Benchmark for Evaluating Speech-to-Text Models on Armenian Speech Recognition Tasks}
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}</code></pre>
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title={ArmBench-ASR: Benchmarking Speech-to-Text Models on Armenian Speech Recognition Tasks},
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author={Metric-AI-Lab},
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year={2026},
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howpublished={\url{https://huggingface.co/spaces/Metric-AI/ArmBench-ASR}},
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note={Benchmark for Evaluating Speech-to-Text Models on Armenian Speech Recognition Tasks}
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}</code></pre>
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<
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<p>Armenian ASR Benchmark is a Metric AI Lab project. The applied AI research lab builds production systems across custom language and vision-language models, multilingual voice agents, Physical AI, retrieval, and analytics—while publishing frontier research and open benchmarks.</p>
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</div>
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<a href="https://metricailab.com" target="_blank" rel="noreferrer">Visit Metric AI Lab <span>↗</span></a>
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</section>
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<section class="acknowledgments">
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<p class="acknowledgments-label">Acknowledgments</p>
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<p>
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We gratefully acknowledge <strong>HiSpeech</strong>, <strong>Talk2Edit</strong>,
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<strong>TBB ASR</strong>, and <strong>Wav.am</strong> for making their systems
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available for evaluation at no cost, and <strong>Infocom</strong> for providing
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Armenian news data used in this benchmark.
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</p>
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</section>
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<footer>
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<span>Armenian ASR Benchmark · v0.1</span>
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<span>A Metric AI Lab project · Built for transparent Armenian speech recognition evaluation.</span>
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</footer>
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</main>
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</body>
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</html>
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<!doctype html>
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<html lang="en">
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<head>
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<meta charset="utf-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1" />
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<meta name="description" content="ArmBench-ASR: Benchmarking Speech-to-Text Models on Armenian Speech Recognition Tasks." />
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<title>ArmBench-ASR</title>
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<script>
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(() => {
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let saved = null;
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try {
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saved = localStorage.getItem("arm-asr-theme");
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} catch (_) {}
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const theme = saved || (matchMedia("(prefers-color-scheme: dark)").matches ? "dark" : "light");
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document.documentElement.dataset.theme = theme;
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})();
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</script>
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<link rel="preconnect" href="https://fonts.googleapis.com" />
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<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin />
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<link href="https://fonts.googleapis.com/css2?family=DM+Sans:wght@400;500;600;700&family=Manrope:wght@600;700;800&display=swap" rel="stylesheet" />
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<link rel="stylesheet" href="style.css" />
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<script src="app.js" defer></script>
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</head>
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<body>
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<main class="shell">
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<header class="hero">
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<div class="hero-tools"><button class="theme-toggle" id="theme-toggle" type="button" aria-label="Switch color theme"><svg class="sun-icon" viewBox="0 0 24 24" aria-hidden="true">
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<circle cx="12" cy="12" r="3.5"></circle>
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<path d="M12 2v2m0 16v2M4.9 4.9l1.4 1.4m11.4 11.4 1.4 1.4M2 12h2m16 0h2M4.9 19.1l1.4-1.4M17.7 6.3l1.4-1.4"></path>
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</svg><svg class="moon-icon" viewBox="0 0 24 24" aria-hidden="true">
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<path d="M20.2 15.1A8.5 8.5 0 0 1 8.9 3.8a8.5 8.5 0 1 0 11.3 11.3Z"></path>
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</svg></button></div>
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<div class="hero-copy">
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<h1><span class="heading-flag" role="img" aria-label="Armenian flag">🇦🇲</span> ArmBench-ASR: Benchmarking Speech-to-Text Models on Armenian Speech Recognition Tasks</h1>
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<p class="lede"><span class="version-badge">v0.1</span></p>
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</div>
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<div class="hero-art" aria-hidden="true"><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span></div>
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</header>
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<nav class="tabs" role="tablist" aria-label="Benchmark sections"><button class="tab is-active" role="tab" aria-selected="true" data-tab="leaderboards"> Leaderboards </button><button class="tab" role="tab" aria-selected="false" data-tab="datasets">Datasets</button><button class="tab" role="tab" aria-selected="false" data-tab="about">About</button></nav>
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<section class="panel is-active matrix-view" id="leaderboards" role="tabpanel">
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<div class="table-heading">
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<div>
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<h2 id="table-title">Overall leaderboard</h2>
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<p id="table-description"> Rank is based on WER. Scores are percentages; lower is better. </p>
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</div>
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<div class="table-tools"><span class="result-count" id="result-count" aria-live="polite"></span></div>
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</div>
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<div class="table-controls" aria-label="Leaderboard display and filters">
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<div class="view-switch" role="group" aria-label="Leaderboard view"><button class="view-button is-active" type="button" data-view="matrix" aria-pressed="true"> All datasets </button><button class="view-button" type="button" data-view="single" aria-pressed="false"> Single dataset </button></div>
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<div class="filter-card">
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<fieldset class="field dataset-field">
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<legend>Dataset</legend>
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<div class="choice-options" id="dataset-options"></div>
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</fieldset>
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<fieldset class="field matrix-metric-field">
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<legend>Metric across all datasets</legend>
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<div class="choice-options" id="matrix-metric-options"></div>
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</fieldset>
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<div class="filter-actions"><button class="color-toggle" id="color-toggle" type="button" aria-pressed="false"><span class="color-swatch good"></span><span class="color-swatch mid"></span><span class="color-swatch bad"></span> Colors </button></div>
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</div>
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</div>
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<div class="table-card">
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<div class="table-scroll">
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<table id="leaderboard-table">
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<thead></thead>
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<tbody></tbody>
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</table>
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</div>
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<div class="empty-state" id="empty-state" hidden>
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<h3>No matching models</h3>
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<p>Select Open or Closed in the Availability column to show models.</p>
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</div>
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</div>
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<div class="table-card">
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<div class="table-scroll">
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<table id="leaderboard-table">
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<thead></thead>
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<tbody></tbody>
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</table>
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</div>
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<div class="empty-state" id="empty-state" hidden>
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<h3>No matching models</h3>
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<p>Select Open or Closed in the Availability column to show models.</p>
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</div>
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</div>
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<section class="comparison-chart" aria-labelledby="comparison-chart-title">
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<div class="comparison-chart-heading">
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<div>
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<h2 id="comparison-chart-title">Model comparison</h2>
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<p>Compare model error rates for one dataset and metric. Lower is better.</p>
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</div>
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<div class="comparison-chart-controls" aria-label="Model comparison filters"><label><span>Dataset</span><select id="chart-dataset" aria-label="Chart dataset"></select></label><label><span>Metric</span><select id="chart-metric" aria-label="Chart metric"></select></label><label><span>Availability</span><select id="chart-availability" aria-label="Chart model availability">
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<option value="All">All models</option>
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<option value="Open">Open only</option>
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<option value="Closed">Closed only</option>
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</select></label></div>
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</div>
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<div class="comparison-chart-card">
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<div class="comparison-bars" id="comparison-bars" aria-live="polite"></div>
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<p class="comparison-chart-empty" id="comparison-chart-empty" hidden>No models match the current filters.</p>
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</div>
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</section>
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<section class="citation-card" aria-labelledby="citation-title">
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<p class="citation-label" id="citation-title">Cite ArmBench-ASR</p>
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<p>If you use ArmBench-ASR in your research, please cite it as follows:</p>
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<pre><code>@misc{armbench-asr,
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title={ArmBench-ASR: Benchmarking Speech-to-Text Models on Armenian Speech Recognition Tasks},
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author={Metric-AI-Lab},
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year={2026},
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howpublished={\url{https://huggingface.co/spaces/Metric-AI/ArmBench-ASR}},
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note={Benchmark for Evaluating Speech-to-Text Models on Armenian Speech Recognition Tasks}
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}</code></pre>
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</section>
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</section>
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<section class="panel" id="datasets" role="tabpanel" hidden>
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<div class="section-intro">
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<h2>Five datasets, one Armenian benchmark</h2>
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<p>10,113 clips and 20.7 hours of speech spanning read, literary, cinematic, and conversational Armenian. Every model is evaluated on the same fixed test material.</p>
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| 119 |
+
</div>
|
| 120 |
+
<div class="dataset-grid">
|
| 121 |
+
<article class="dataset-card">
|
| 122 |
+
<div class="dataset-card-top"><span>01</span><span class="dataset-tag public">Public</span></div>
|
| 123 |
+
<h3><a class="dataset-source" href="https://mozilladatacollective.com/datasets/cmqinsp2y00xsnr07ra8gxfoi" target="_blank" rel="noreferrer">Common Voice 26 <span>↗</span></a></h3>
|
| 124 |
+
<p>Mozilla Common Voice Scripted Speech 26.0 for Armenian, using the full <code>hy-AM</code> test split released in June 2026.</p>
|
| 125 |
+
<dl class="dataset-meta">
|
| 126 |
+
<div>
|
| 127 |
+
<dt>Samples</dt>
|
| 128 |
+
<dd>6,892</dd>
|
| 129 |
+
</div>
|
| 130 |
+
<div>
|
| 131 |
+
<dt>Audio</dt>
|
| 132 |
+
<dd>10.8 h</dd>
|
| 133 |
+
</div>
|
| 134 |
+
<div>
|
| 135 |
+
<dt>Style</dt>
|
| 136 |
+
<dd>Read speech</dd>
|
| 137 |
+
</div>
|
| 138 |
+
</dl>
|
| 139 |
+
</article>
|
| 140 |
+
<article class="dataset-card">
|
| 141 |
+
<div class="dataset-card-top"><span>02</span><span class="dataset-tag public">Public</span></div>
|
| 142 |
+
<h3><a class="dataset-source" href="https://huggingface.co/datasets/google/fleurs" target="_blank" rel="noreferrer">FLEURS <span>↗</span></a></h3>
|
| 143 |
+
<p>Google FLEURS Armenian (<code>hy_am</code>) test split. Raw transcriptions retain punctuation and capitalization for strict scoring, with some <a href="https://huggingface.co/datasets/Metric-AI/fleurs-corrections" target="_blank" rel="noreferrer">manual corrections</a> applied.</p>
|
| 144 |
+
<dl class="dataset-meta">
|
| 145 |
+
<div>
|
| 146 |
+
<dt>Samples</dt>
|
| 147 |
+
<dd>932</dd>
|
| 148 |
+
</div>
|
| 149 |
+
<div>
|
| 150 |
+
<dt>Audio</dt>
|
| 151 |
+
<dd>3.0 h</dd>
|
| 152 |
+
</div>
|
| 153 |
+
<div>
|
| 154 |
+
<dt>Style</dt>
|
| 155 |
+
<dd>Read speech</dd>
|
| 156 |
+
</div>
|
| 157 |
+
</dl>
|
| 158 |
+
</article>
|
| 159 |
+
<article class="dataset-card">
|
| 160 |
+
<div class="dataset-card-top"><span>03</span><span class="dataset-tag private">Private</span></div>
|
| 161 |
+
<h3>Poems</h3>
|
| 162 |
+
<p>Read Armenian poetry with background music, literary vocabulary, expressive phrasing, and text structures underrepresented in general ASR sets.</p>
|
| 163 |
+
<dl class="dataset-meta">
|
| 164 |
+
<div>
|
| 165 |
+
<dt>Samples</dt>
|
| 166 |
+
<dd>969</dd>
|
| 167 |
+
</div>
|
| 168 |
+
<div>
|
| 169 |
+
<dt>Audio</dt>
|
| 170 |
+
<dd>3.3 h</dd>
|
| 171 |
+
</div>
|
| 172 |
+
<div>
|
| 173 |
+
<dt>Style</dt>
|
| 174 |
+
<dd>Literary</dd>
|
| 175 |
+
</div>
|
| 176 |
+
</dl>
|
| 177 |
+
</article>
|
| 178 |
+
<article class="dataset-card">
|
| 179 |
+
<div class="dataset-card-top"><span>04</span><span class="dataset-tag private">Private</span></div>
|
| 180 |
+
<h3>Movies</h3>
|
| 181 |
+
<p>Armenian movie dialogue with conversational delivery, produced-media acoustics, and occasional background noise.</p>
|
| 182 |
+
<dl class="dataset-meta">
|
| 183 |
+
<div>
|
| 184 |
+
<dt>Samples</dt>
|
| 185 |
+
<dd>820</dd>
|
| 186 |
+
</div>
|
| 187 |
+
<div>
|
| 188 |
+
<dt>Audio</dt>
|
| 189 |
+
<dd>1.7 h</dd>
|
| 190 |
+
</div>
|
| 191 |
+
<div>
|
| 192 |
+
<dt>Style</dt>
|
| 193 |
+
<dd>Dialogue</dd>
|
| 194 |
+
</div>
|
| 195 |
+
</dl>
|
| 196 |
+
</article>
|
| 197 |
+
<article class="dataset-card">
|
| 198 |
+
<div class="dataset-card-top"><span>05</span><span class="dataset-tag private">Private</span></div>
|
| 199 |
+
<h3>News</h3>
|
| 200 |
+
<p>A compact Armenian news dataset recited by a speaker, designed to evaluate clear narrated speech beyond standard public test sets.</p>
|
| 201 |
+
<dl class="dataset-meta">
|
| 202 |
+
<div>
|
| 203 |
+
<dt>Samples</dt>
|
| 204 |
+
<dd>500</dd>
|
| 205 |
+
</div>
|
| 206 |
+
<div>
|
| 207 |
+
<dt>Audio</dt>
|
| 208 |
+
<dd>1.9 h</dd>
|
| 209 |
+
</div>
|
| 210 |
+
<div>
|
| 211 |
+
<dt>Style</dt>
|
| 212 |
+
<dd>Narrated news</dd>
|
| 213 |
+
</div>
|
| 214 |
+
</dl>
|
| 215 |
+
</article>
|
| 216 |
+
</div>
|
| 217 |
+
<section class="citation-card" aria-labelledby="citation-title">
|
| 218 |
+
<p class="citation-label" id="citation-title">Cite ArmBench-ASR</p>
|
| 219 |
+
<p>If you use ArmBench-ASR in your research, please cite it as follows:</p>
|
| 220 |
+
<pre><code>@misc{armbench-asr,
|
| 221 |
title={ArmBench-ASR: Benchmarking Speech-to-Text Models on Armenian Speech Recognition Tasks},
|
| 222 |
author={Metric-AI-Lab},
|
| 223 |
year={2026},
|
| 224 |
howpublished={\url{https://huggingface.co/spaces/Metric-AI/ArmBench-ASR}},
|
| 225 |
note={Benchmark for Evaluating Speech-to-Text Models on Armenian Speech Recognition Tasks}
|
| 226 |
}</code></pre>
|
| 227 |
+
</section>
|
| 228 |
+
</section>
|
| 229 |
+
<section class="panel" id="about" role="tabpanel" hidden>
|
| 230 |
+
<div class="about-grid">
|
| 231 |
+
<div class="section-intro">
|
| 232 |
+
<h2>Reading the benchmark</h2>
|
| 233 |
+
<p> Armenian ASR Benchmark compares automatic speech recognition systems on a varied Armenian evaluation suite. Every score is an error rate, so lower values are better. </p>
|
| 234 |
+
<p> The benchmark aims to bring clarity to the Armenian ASR landscape, make model comparisons easier, and help model creators identify strengths, gaps, and opportunities for meaningful improvement. </p>
|
| 235 |
+
</div>
|
| 236 |
+
<div class="definition-list">
|
| 237 |
+
<article><strong>WER</strong><span>Word error rate after strict, punctuation-preserving preprocessing.</span></article>
|
| 238 |
+
<article><strong>CER</strong><span>Character error rate after strict, punctuation-preserving preprocessing.</span></article>
|
| 239 |
+
<article><strong>WER-norm</strong><span>Word error rate after text normalization.</span></article>
|
| 240 |
+
<article><strong>CER-norm</strong><span>Character error rate after text normalization.</span></article>
|
| 241 |
+
</div>
|
| 242 |
+
</div>
|
| 243 |
+
<div class="note"><strong>Availability</strong>
|
| 244 |
+
<p><b>Open</b> means model weights are publicly available. <b>Closed</b> means access is provided through a hosted product or API.</p>
|
| 245 |
+
</div>
|
| 246 |
+
<div class="note"><strong>API settings</strong>
|
| 247 |
+
<p>Hosted systems use fixed model identifiers and transcription-only prompts. Evaluated Gemini runs use temperature 0, a 1,000-token output cap, and audio limited to 40 seconds. Thinking is disabled or set to the lowest applicable level: budget 0 for Gemini 2.5 Flash, budget 128 for Gemini 2.5 Pro, and <b>MINIMAL</b> for Gemini 3.1 Flash Lite, 3.5 Flash Lite, and 3.6 Flash.</p>
|
| 248 |
+
</div>
|
| 249 |
+
<div class="note"><strong>Text cleaning</strong>
|
| 250 |
+
<p>References and predictions are processed with the same deterministic pipeline. Strict scoring standardizes punctuation, spacing, capitalization, and Unicode; normalized scoring additionally reduces orthographic and formatting differences while preserving Armenian, English, Russian letters, digits, and recognized clock times. Both <b>WER / CER</b> and <b>WER-norm / CER-norm</b> are reported.</p>
|
| 251 |
+
</div>
|
| 252 |
+
<section class="lab-card">
|
| 253 |
+
<div>
|
| 254 |
+
<h2>About Us</h2>
|
| 255 |
+
<p>Armenian ASR Benchmark is a Metric AI Lab project. The applied AI research lab builds production systems across custom language and vision-language models, multilingual voice agents, Physical AI, retrieval, and analytics—while publishing frontier research and open benchmarks.</p>
|
| 256 |
+
</div><a href="https://metricailab.com" target="_blank" rel="noreferrer">Visit Metric AI Lab <span>↗</span></a>
|
| 257 |
+
</section>
|
| 258 |
+
<section class="acknowledgments">
|
| 259 |
+
<p class="acknowledgments-label">Acknowledgments</p>
|
| 260 |
+
<p> We gratefully acknowledge <strong>HiSpeech</strong>, <strong>Talk2Edit</strong>, <strong>TBB ASR</strong>, and <strong>Wav.am</strong> for making their systems available for evaluation at no cost, and <strong>Infocom</strong> for providing Armenian news data used in this benchmark. </p>
|
| 261 |
+
</section>
|
| 262 |
+
<footer><span>Armenian ASR Benchmark · v0.1</span><span>A Metric AI Lab project · Built for transparent Armenian speech recognition evaluation.</span></footer>
|
| 263 |
+
</main>
|
| 264 |
+
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