{ "schema": 1, "language": "en", "lang_code": "a", "dialect": "us", "voice": "am_echo", "speed": 0.94, "sample_rate": 24000, "total_duration": 126.39, "media_sha256": "fba54f235275627c0bb37485d3579d0782f45889b8d254a0e07b763c0bf98f4d", "media_bytes": 811170, "render_fingerprint": "25c31b61e7cf531876c9fcd644037ec5f0422f0cfff7ac460409fe6c1d6c4e72", "render_inputs": { "renderer": "render_all_voices-v4", "lesson": "11_classify_ml", "language": "en", "lang_code": "a", "dialect": "us", "voice": "am_echo", "speed": 0.94, "scenes": [ { "narration": "Classify ML trains a classical model on per-object measurements. The console reports database loading, feature preparation, validation, importance, predictions, and errors.", "speech_text": [ "[Classify](/klˈæsəfI/) ML trains a classical model on per-object measurements.", "The console reports database loading, feature preparation, validation, importance, predictions, and errors." ], "authored_hold": 0.7, "resolved_hold": 0.52, "speed_multiplier": 1.0, "effective_speed": 0.94 }, { "narration": "Labels and Classes selects the measurement project, label field, positive and negative values, and experimental grouping. Verify the biological meaning of that mapping before fitting a model.", "speech_text": [ "Labels and Classes selects the measurement project, label field, positive and negative values, and experimental grouping.", "Verify the biological meaning of that mapping before fitting a model." ], "authored_hold": 0.7, "resolved_hold": 0.52, "speed_multiplier": 1.0, "effective_speed": 0.94 }, { "narration": "Start with Essentials and audit changes in Modified. Open All only for controls the analysis needs, and save a Recipe for repeated runs.", "speech_text": [ "Start with Essentials and audit changes in Modified.", "Open All only for controls the analysis needs, and save a Recipe for repeated runs." ], "authored_hold": 0.7, "resolved_hold": 0.52, "speed_multiplier": 1.0, "effective_speed": 0.94 }, { "narration": "Feature Preparation selects the channel of interest and removes excluded, invalid, low-variance, highly correlated, or poorly supported measurements before training.", "speech_text": [ "Feature Preparation selects the channel of interest and removes excluded, invalid, low-variance, highly correlated, or poorly supported measurements before training." ], "authored_hold": 0.7, "resolved_hold": 0.52, "speed_multiplier": 1.0, "effective_speed": 0.94 }, { "narration": "Plate and Batch Correction can normalize each plate against its controls. Use a correction that preserves the biological contrast and can be applied consistently to future data.", "speech_text": [ "Plate and Batch Correction can normalize each plate against its controls.", "Use a correction that preserves the biological contrast and can be applied consistently to future data." ], "authored_hold": 0.7, "resolved_hold": 0.52, "speed_multiplier": 1.0, "effective_speed": 0.94 }, { "narration": "Classifier and Validation selects the estimator, complexity, held-out split, and cross-validation behavior. Group related objects by plate or well to avoid leakage.", "speech_text": [ "[Classifier](/klˈæsəfIəɹ/) and Validation selects the estimator, complexity, held-out split, and cross-validation behavior.", "Group related objects by plate or well to avoid leakage." ], "authored_hold": 0.7, "resolved_hold": 0.52, "speed_multiplier": 1.0, "effective_speed": 0.94 }, { "narration": "Feature Selection and Importance prunes the final feature set and estimates which measurements support the classifier. Interpret importance only after held-out performance is acceptable.", "speech_text": [ "Feature Selection and Importance prunes the final feature set and estimates which measurements support the [classifier](/klˈæsəfIəɹ/).", "Interpret importance only after held-out performance is acceptable." ], "authored_hold": 0.7, "resolved_hold": 0.52, "speed_multiplier": 1.0, "effective_speed": 0.94 }, { "narration": "Output and Database controls whether probabilities, class calls, model files, and selected features are saved or written back to the measurement project.", "speech_text": [ "Output and Database controls whether probabilities, class calls, model files, and selected features are saved or written back to the measurement project." ], "authored_hold": 0.7, "resolved_hold": 0.52, "speed_multiplier": 1.0, "effective_speed": 0.94 }, { "narration": "Hyperparameter Search is a mini workbench for comparing a focused set of model choices with grouped folds. The results table ranks completed trials and shows their variation.", "speech_text": [ "hyper-parameter Search is a mini workbench for comparing a focused set of model choices with grouped folds.", "The results table ranks completed trials and shows their variation." ], "authored_hold": 0.7, "resolved_hold": 0.52, "speed_multiplier": 1.0, "effective_speed": 0.94 }, { "narration": "Search Settings defines candidate values, trial budget, folds, seed, and ranking metric. Keep the search space small enough to explain and reproduce.", "speech_text": [ "Search Settings defines candidate values, trial budget, folds, seed, and ranking metric.", "Keep the search space small enough to explain and reproduce." ], "authored_hold": 0.7, "resolved_hold": 0.52, "speed_multiplier": 1.0, "effective_speed": 0.94 }, { "narration": "Run validates controls, prepares features, applies any plate correction, evaluates the classifier, calculates importance, and saves enabled outputs. Review held-out and per-plate behavior before using predictions biologically.", "speech_text": [ "Run validates controls, prepares features, applies any plate correction, evaluates the [classifier](/klˈæsəfIəɹ/), calculates importance, and saves enabled outputs.", "Review held-out and per-plate behavior before using predictions biologically." ], "authored_hold": 0.7, "resolved_hold": 0.52, "speed_multiplier": 1.0, "effective_speed": 0.94 } ], "assembly": { "version": "2026-08-11-natural-sentences-v1", "sample_rate": 24000, "lead_silence_seconds": 0.1, "tail_silence_seconds": 0.18, "sentence_pause_seconds": 0.12, "scene_hold_min_seconds": 0.32, "scene_hold_max_seconds": 0.52, "default_scene_hold_seconds": 0.42, "vad_frame_seconds": 0.005, "vad_peak_ratio": 0.002, "vad_absolute_floor": 2e-05 }, "cadence_profile": { "version": "2026-08-11-af-heart-scene-cadence-v6", "sha256": "4d728d67e73eea7e6203878879992f9050ae4a2677d717efdd68545104eb7812", "bytes": 23008, "enabled": false, "targets": { "slow_wpm": 125.0, "fast_wpm": 145.0, "calibration_wpm": 150.0 }, "safe_multiplier_bounds": { "minimum": 0.68, "maximum": 1.18 } }, "mastering": { "filters": [ "loudnorm=I=-16:TP=-3:LRA=11", "loudnorm=I=-16:TP=-5:LRA=11,alimiter=limit=0.7:attack=5:release=50:level=disabled", "loudnorm=I=-16:TP=-5:LRA=11,alimiter=limit=0.5:attack=5:release=50:level=disabled" ], "codec": "aac", "bitrate": "48k", "channels": 1, "maximum_decoded_true_peak_dbfs": -1.0 }, "pronunciation": { "role": "pronunciation_profile", "version": "2026-08-11-en-natural-v6", "sha256": "1fbaa615cfa904094bdef5cba963539f0e8bec5927192a76b0d503e90c4bb83e", "bytes": 13263 }, "synthesis_runtime": { "model": { "repository": "hexgrad/Kokoro-82M", "snapshot": "f3ff3571791e39611d31c381e3a41a3af07b4987", "config": { "role": "kokoro_config", "name": "14a726edd3718279eac426630879ff743955b16a", "bytes": 2351, "sha256": "5abb01e2403b072bf03d04fde160443e209d7a0dad49a423be15196b9b43c17f" }, "weights": { "role": "kokoro_weights", "name": "496dba118d1a58f5f3db2efc88dbdc216e0483fc89fe6e47ee1f2c53f18ad1e4", "bytes": 327212226, "sha256": "496dba118d1a58f5f3db2efc88dbdc216e0483fc89fe6e47ee1f2c53f18ad1e4" } }, "voice_pack": { "role": "kokoro_voice_pack", "name": "8bcfdc852bc985fb45c396c561e571ffb9183930071f962f1b50df5c97b161e8", "bytes": 523420, "sha256": "8bcfdc852bc985fb45c396c561e571ffb9183930071f962f1b50df5c97b161e8", "tensor_sha256": "3968b92c3c4cd1c4416dbded36c13eaa388a90d5788d02a13e4d781f5f8cf3c3", "loaded_tensor_sha256": "3968b92c3c4cd1c4416dbded36c13eaa388a90d5788d02a13e4d781f5f8cf3c3" }, "software": { "kokoro": "0.9.4", "misaki": "0.9.4", "torch": "2.6.0", "soundfile": "0.14.0", "python": "3.12.4", "implementation": "cpython" }, "inference": { "device": "cuda" }, "mastering_tool": { "version": "ffmpeg version 6.1.1-3ubuntu5+esm10 Copyright (c) 2000-2023 the FFmpeg developers", "version_output_sha256": "92dfb2468e6f5f06919b5433c0f14459ac19b81b1bc2d9fdceb83c6ad42e37b5", "executable": { "role": "ffmpeg_executable", "name": "ffmpeg", "bytes": 342488, "sha256": "ad63ef3f2f18fa92e89f0ec2bde6941e81f83724c8d265414cb659c28077392d" } } } }, "scenes": [ { "scene": 1, "speech_start": 0.0, "speech_end": 11.475, "scene_end": 11.995, "duration": 11.995, "text": "Classify ML trains a classical model on per-object measurements. The console reports database loading, feature preparation, validation, importance, predictions, and errors.", "speech_text": "[Classify](/klˈæsəfI/) ML trains a classical model on per-object measurements. The console reports database loading, feature preparation, validation, importance, predictions, and errors.", "phonemes": "klˈæsəfI ˌɛmˈɛl tɹˈAnz ɐ klˈæsəkᵊl mˈɑdᵊl ˌɔn pɜɹˈɑbʤəkt mˈɛʒəɹmᵊnts. ðə kˈɑnsˌOl ɹəpˈɔɹts dˈæTəbˌAs lˈOdɪŋ, fˈiʧəɹ pɹˌɛpəɹˈAʃən, vˌælɪdˈAʃən, ɪmpˈɔɹtᵊns, pɹidˈɪkʃənz, ænd ˈɛɹəɹz.", "authored_hold_after": 0.7, "hold_after": 0.52, "base_speed": 0.94, "speed_multiplier": 1.0, "effective_speed": 0.94, "sentences": [ { "sentence": 1, "speech_start": 0.0, "speech_end": 4.65, "audible_start": 0.1, "audible_end": 4.47, "duration": 4.65, "gap_from_previous": null, "trimmed_lead": 0.175, "trimmed_tail": 0.425, "text": "Classify ML trains a classical model on per-object measurements.", "speech_text": "[Classify](/klˈæsəfI/) ML trains a classical model on per-object measurements.", "phonemes": "klˈæsəfI ˌɛmˈɛl tɹˈAnz ɐ klˈæsəkᵊl mˈɑdᵊl ˌɔn pɜɹˈɑbʤəkt mˈɛʒəɹmᵊnts." }, { "sentence": 2, "speech_start": 4.77, "speech_end": 11.475, "audible_start": 4.87, "audible_end": 11.295, "duration": 6.705, "gap_from_previous": 0.4, "trimmed_lead": 0.17, "trimmed_tail": 0.5, "text": "The console reports database loading, feature preparation, validation, importance, predictions, and errors.", "speech_text": "The console reports database loading, feature preparation, validation, importance, predictions, and errors.", "phonemes": "ðə kˈɑnsˌOl ɹəpˈɔɹts dˈæTəbˌAs lˈOdɪŋ, fˈiʧəɹ pɹˌɛpəɹˈAʃən, vˌælɪdˈAʃən, ɪmpˈɔɹtᵊns, pɹidˈɪkʃənz, ænd ˈɛɹəɹz." } ] }, { "scene": 2, "speech_start": 11.995, "speech_end": 24.06, "scene_end": 24.58, "duration": 12.584999999999999, "text": "Labels and Classes selects the measurement project, label field, positive and negative values, and experimental grouping. Verify the biological meaning of that mapping before fitting a model.", "speech_text": "Labels and Classes selects the measurement project, label field, positive and negative values, and experimental grouping. Verify the biological meaning of that mapping before fitting a model.", "phonemes": "lˈAbəlz ænd klˈæsᵻz səlˈɛkts ðə mˈɛʒəɹmᵊnt pɹˈɑʤˌɛkt, lˈAbəl fˈild, pˈɑzəTɪv ænd nˈɛɡəTɪv vˈæljuz, ænd ɪkspˌɛɹəmˈɛntᵊl ɡɹˈupɪŋ. vˈɛɹəfˌI ðə bˌIəlˈɑʤəkᵊl mˈinɪŋ ʌv ðˈæt mˈæpɪŋ bəfˈɔɹ fˈɪTɪŋ ɐ mˈɑdᵊl.", "authored_hold_after": 0.7, "hold_after": 0.52, "base_speed": 0.94, "speed_multiplier": 1.0, "effective_speed": 0.94, "sentences": [ { "sentence": 1, "speech_start": 11.995, "speech_end": 19.435, "audible_start": 12.094999999999999, "audible_end": 19.255, "duration": 7.44, "gap_from_previous": null, "trimmed_lead": 0.17, "trimmed_tail": 0.54, "text": "Labels and Classes selects the measurement project, label field, positive and negative values, and experimental grouping.", "speech_text": "Labels and Classes selects the measurement project, label field, positive and negative values, and experimental grouping.", "phonemes": "lˈAbəlz ænd klˈæsᵻz səlˈɛkts ðə mˈɛʒəɹmᵊnt pɹˈɑʤˌɛkt, lˈAbəl fˈild, pˈɑzəTɪv ænd nˈɛɡəTɪv vˈæljuz, ænd ɪkspˌɛɹəmˈɛntᵊl ɡɹˈupɪŋ." }, { "sentence": 2, "speech_start": 19.555, "speech_end": 24.06, "audible_start": 19.655, "audible_end": 23.88, "duration": 4.505, "gap_from_previous": 0.4, "trimmed_lead": 0.155, "trimmed_tail": 0.465, "text": "Verify the biological meaning of that mapping before fitting a model.", "speech_text": "Verify the biological meaning of that mapping before fitting a model.", "phonemes": "vˈɛɹəfˌI ðə bˌIəlˈɑʤəkᵊl mˈinɪŋ ʌv ðˈæt mˈæpɪŋ bəfˈɔɹ fˈɪTɪŋ ɐ mˈɑdᵊl." } ] }, { "scene": 3, "speech_start": 24.58, "speech_end": 34.045, "scene_end": 34.565000000000005, "duration": 9.985000000000007, "text": "Start with Essentials and audit changes in Modified. Open All only for controls the analysis needs, and save a Recipe for repeated runs.", "speech_text": "Start with Essentials and audit changes in Modified. Open All only for controls the analysis needs, and save a Recipe for repeated runs.", "phonemes": "stˈɑɹt wɪð əsˈɛnʧᵊlz ænd ˈɔdət ʧˈAnʤᵻz ɪn mˈɑdəfˌId. ˈOpᵊn ˈɔl ˈOnli fɔɹ kəntɹˈOlz ði ənˈæləsɪs nˈidz, ænd sˈAv ɐ ɹˈɛsəpˌi fɔɹ ɹəpˈiTᵻd ɹˈʌnz.", "authored_hold_after": 0.7, "hold_after": 0.52, "base_speed": 0.94, "speed_multiplier": 1.0, "effective_speed": 0.94, "sentences": [ { "sentence": 1, "speech_start": 24.58, "speech_end": 28.25, "audible_start": 24.68, "audible_end": 28.07, "duration": 3.67, "gap_from_previous": null, "trimmed_lead": 0.145, "trimmed_tail": 0.46, "text": "Start with Essentials and audit changes in Modified.", "speech_text": "Start with Essentials and audit changes in Modified.", "phonemes": "stˈɑɹt wɪð əsˈɛnʧᵊlz ænd ˈɔdət ʧˈAnʤᵻz ɪn mˈɑdəfˌId." }, { "sentence": 2, "speech_start": 28.369999999999997, "speech_end": 34.045, "audible_start": 28.47, "audible_end": 33.864999999999995, "duration": 5.675, "gap_from_previous": 0.4, "trimmed_lead": 0.18, "trimmed_tail": 0.495, "text": "Open All only for controls the analysis needs, and save a Recipe for repeated runs.", "speech_text": "Open All only for controls the analysis needs, and save a Recipe for repeated runs.", "phonemes": "ˈOpᵊn ˈɔl ˈOnli fɔɹ kəntɹˈOlz ði ənˈæləsɪs nˈidz, ænd sˈAv ɐ ɹˈɛsəpˌi fɔɹ ɹəpˈiTᵻd ɹˈʌnz." } ] }, { "scene": 4, "speech_start": 34.565000000000005, "speech_end": 44.35000000000001, "scene_end": 44.87000000000001, "duration": 10.305000000000007, "text": "Feature Preparation selects the channel of interest and removes excluded, invalid, low-variance, highly correlated, or poorly supported measurements before training.", "speech_text": "Feature Preparation selects the channel of interest and removes excluded, invalid, low-variance, highly correlated, or poorly supported measurements before training.", "phonemes": "fˈiʧəɹ pɹˌɛpəɹˈAʃən səlˈɛkts ðə ʧˈænᵊl ʌv ˈɪntɹəst ænd ɹəmˈuvz ɪksklˈudᵻd, ɪnvˈælɪd, lˌOvˈɛɹiəns, hˈIli kˈɔɹəlˌATᵻd, ɔɹ pˈʊɹli səpˈɔɹTᵻd mˈɛʒəɹmᵊnts bəfˈɔɹ tɹˈAnɪŋ.", "authored_hold_after": 0.7, "hold_after": 0.52, "base_speed": 0.94, "speed_multiplier": 1.0, "effective_speed": 0.94, "sentences": [ { "sentence": 1, "speech_start": 34.565000000000005, "speech_end": 44.35000000000001, "audible_start": 34.665000000000006, "audible_end": 44.17, "duration": 9.785, "gap_from_previous": null, "trimmed_lead": 0.155, "trimmed_tail": 0.56, "text": "Feature Preparation selects the channel of interest and removes excluded, invalid, low-variance, highly correlated, or poorly supported measurements before training.", "speech_text": "Feature Preparation selects the channel of interest and removes excluded, invalid, low-variance, highly correlated, or poorly supported measurements before training.", "phonemes": "fˈiʧəɹ pɹˌɛpəɹˈAʃən səlˈɛkts ðə ʧˈænᵊl ʌv ˈɪntɹəst ænd ɹəmˈuvz ɪksklˈudᵻd, ɪnvˈælɪd, lˌOvˈɛɹiəns, hˈIli kˈɔɹəlˌATᵻd, ɔɹ pˈʊɹli səpˈɔɹTᵻd mˈɛʒəɹmᵊnts bəfˈɔɹ tɹˈAnɪŋ." } ] }, { "scene": 5, "speech_start": 44.87000000000001, "speech_end": 56.11500000000001, "scene_end": 56.63500000000001, "duration": 11.765, "text": "Plate and Batch Correction can normalize each plate against its controls. Use a correction that preserves the biological contrast and can be applied consistently to future data.", "speech_text": "Plate and Batch Correction can normalize each plate against its controls. Use a correction that preserves the biological contrast and can be applied consistently to future data.", "phonemes": "plˈAt ænd bˈæʧ kəɹˈɛkʃən kæn nˈɔɹməlˌIz ˈiʧ plˈAt əɡˈɛnst ɪts kəntɹˈOlz. jˈuz ɐ kəɹˈɛkʃən ðæt pɹəzˈɜɹvz ðə bˌIəlˈɑʤəkᵊl kˈɑntɹˌæst ænd kæn bi əplˈId kənsˈɪstəntli tə fjˈuʧəɹ dˈATə.", "authored_hold_after": 0.7, "hold_after": 0.52, "base_speed": 0.94, "speed_multiplier": 1.0, "effective_speed": 0.94, "sentences": [ { "sentence": 1, "speech_start": 44.87000000000001, "speech_end": 49.46000000000001, "audible_start": 44.97000000000001, "audible_end": 49.280000000000015, "duration": 4.59, "gap_from_previous": null, "trimmed_lead": 0.16, "trimmed_tail": 0.45, "text": "Plate and Batch Correction can normalize each plate against its controls.", "speech_text": "Plate and Batch Correction can normalize each plate against its controls.", "phonemes": "plˈAt ænd bˈæʧ kəɹˈɛkʃən kæn nˈɔɹməlˌIz ˈiʧ plˈAt əɡˈɛnst ɪts kəntɹˈOlz." }, { "sentence": 2, "speech_start": 49.58000000000001, "speech_end": 56.11500000000001, "audible_start": 49.680000000000014, "audible_end": 55.93500000000001, "duration": 6.535, "gap_from_previous": 0.4, "trimmed_lead": 0.165, "trimmed_tail": 0.525, "text": "Use a correction that preserves the biological contrast and can be applied consistently to future data.", "speech_text": "Use a correction that preserves the biological contrast and can be applied consistently to future data.", "phonemes": "jˈuz ɐ kəɹˈɛkʃən ðæt pɹəzˈɜɹvz ðə bˌIəlˈɑʤəkᵊl kˈɑntɹˌæst ænd kæn bi əplˈId kənsˈɪstəntli tə fjˈuʧəɹ dˈATə." } ] }, { "scene": 6, "speech_start": 56.63500000000001, "speech_end": 67.58000000000001, "scene_end": 68.10000000000001, "duration": 11.464999999999996, "text": "Classifier and Validation selects the estimator, complexity, held-out split, and cross-validation behavior. Group related objects by plate or well to avoid leakage.", "speech_text": "[Classifier](/klˈæsəfIəɹ/) and Validation selects the estimator, complexity, held-out split, and cross-validation behavior. Group related objects by plate or well to avoid leakage.", "phonemes": "klˈæsəfIəɹ ænd vˌælɪdˈAʃən səlˈɛkts ði ˈɛstəmˌATəɹ, kəmplˈɛksəTi, hˈɛldˌWt splˈɪt, ænd kɹˌɔsvˌælɪdˈAʃən bəhˈAvjəɹ. ɡɹˈup ɹəlˈATᵻd ˈɑbʤəkts bI plˈAt ɔɹ wˈɛl tʊ əvˈYd lˈikɪʤ.", "authored_hold_after": 0.7, "hold_after": 0.52, "base_speed": 0.94, "speed_multiplier": 1.0, "effective_speed": 0.94, "sentences": [ { "sentence": 1, "speech_start": 56.63500000000001, "speech_end": 63.56000000000001, "audible_start": 56.735000000000014, "audible_end": 63.38000000000001, "duration": 6.925, "gap_from_previous": null, "trimmed_lead": 0.16, "trimmed_tail": 0.54, "text": "Classifier and Validation selects the estimator, complexity, held-out split, and cross-validation behavior.", "speech_text": "[Classifier](/klˈæsəfIəɹ/) and Validation selects the estimator, complexity, held-out split, and cross-validation behavior.", "phonemes": "klˈæsəfIəɹ ænd vˌælɪdˈAʃən səlˈɛkts ði ˈɛstəmˌATəɹ, kəmplˈɛksəTi, hˈɛldˌWt splˈɪt, ænd kɹˌɔsvˌælɪdˈAʃən bəhˈAvjəɹ." }, { "sentence": 2, "speech_start": 63.680000000000014, "speech_end": 67.58000000000001, "audible_start": 63.780000000000015, "audible_end": 67.4, "duration": 3.9, "gap_from_previous": 0.4, "trimmed_lead": 0.16, "trimmed_tail": 0.44, "text": "Group related objects by plate or well to avoid leakage.", "speech_text": "Group related objects by plate or well to avoid leakage.", "phonemes": "ɡɹˈup ɹəlˈATᵻd ˈɑbʤəkts bI plˈAt ɔɹ wˈɛl tʊ əvˈYd lˈikɪʤ." } ] }, { "scene": 7, "speech_start": 68.10000000000001, "speech_end": 79.33000000000001, "scene_end": 79.85000000000001, "duration": 11.75, "text": "Feature Selection and Importance prunes the final feature set and estimates which measurements support the classifier. Interpret importance only after held-out performance is acceptable.", "speech_text": "Feature Selection and Importance prunes the final feature set and estimates which measurements support the [classifier](/klˈæsəfIəɹ/). Interpret importance only after held-out performance is acceptable.", "phonemes": "fˈiʧəɹ səlˈɛkʃən ænd ɪmpˈɔɹtᵊns pɹˈunz ðə fˈInᵊl fˈiʧəɹ sˈɛt ænd ˈɛstəməts wˌɪʧ mˈɛʒəɹmᵊnts səpˈɔɹt ðə klˈæsəfIəɹ. ɪntˈɜɹpɹət ɪmpˈɔɹtᵊns ˈOnli ˈæftəɹ hˈɛldˌWt pəɹfˈɔɹməns ɪz əksˈɛptəbᵊl.", "authored_hold_after": 0.7, "hold_after": 0.52, "base_speed": 0.94, "speed_multiplier": 1.0, "effective_speed": 0.94, "sentences": [ { "sentence": 1, "speech_start": 68.10000000000001, "speech_end": 74.83500000000001, "audible_start": 68.2, "audible_end": 74.655, "duration": 6.735, "gap_from_previous": null, "trimmed_lead": 0.16, "trimmed_tail": 0.53, "text": "Feature Selection and Importance prunes the final feature set and estimates which measurements support the classifier.", "speech_text": "Feature Selection and Importance prunes the final feature set and estimates which measurements support the [classifier](/klˈæsəfIəɹ/).", "phonemes": "fˈiʧəɹ səlˈɛkʃən ænd ɪmpˈɔɹtᵊns pɹˈunz ðə fˈInᵊl fˈiʧəɹ sˈɛt ænd ˈɛstəməts wˌɪʧ mˈɛʒəɹmᵊnts səpˈɔɹt ðə klˈæsəfIəɹ." }, { "sentence": 2, "speech_start": 74.95500000000001, "speech_end": 79.33000000000001, "audible_start": 75.055, "audible_end": 79.15, "duration": 4.375, "gap_from_previous": 0.4, "trimmed_lead": 0.16, "trimmed_tail": 0.465, "text": "Interpret importance only after held-out performance is acceptable.", "speech_text": "Interpret importance only after held-out performance is acceptable.", "phonemes": "ɪntˈɜɹpɹət ɪmpˈɔɹtᵊns ˈOnli ˈæftəɹ hˈɛldˌWt pəɹfˈɔɹməns ɪz əksˈɛptəbᵊl." } ] }, { "scene": 8, "speech_start": 79.85000000000001, "speech_end": 89.135, "scene_end": 89.655, "duration": 9.804999999999993, "text": "Output and Database controls whether probabilities, class calls, model files, and selected features are saved or written back to the measurement project.", "speech_text": "Output and Database controls whether probabilities, class calls, model files, and selected features are saved or written back to the measurement project.", "phonemes": "ˈWtpˌʊt ænd dˈæTəbˌAs kəntɹˈOlz wˈɛðəɹ pɹˌɑbəbˈɪləTiz, klˈæs kˈɔlz, mˈɑdᵊl fˈIlz, ænd səlˈɛktᵻd fˈiʧəɹz ɑɹ sˈAvd ɔɹ ɹˈɪtn bˈæk tə ðə mˈɛʒəɹmᵊnt pɹˈɑʤˌɛkt.", "authored_hold_after": 0.7, "hold_after": 0.52, "base_speed": 0.94, "speed_multiplier": 1.0, "effective_speed": 0.94, "sentences": [ { "sentence": 1, "speech_start": 79.85000000000001, "speech_end": 89.135, "audible_start": 79.95, "audible_end": 88.95500000000001, "duration": 9.285, "gap_from_previous": null, "trimmed_lead": 0.17, "trimmed_tail": 0.52, "text": "Output and Database controls whether probabilities, class calls, model files, and selected features are saved or written back to the measurement project.", "speech_text": "Output and Database controls whether probabilities, class calls, model files, and selected features are saved or written back to the measurement project.", "phonemes": "ˈWtpˌʊt ænd dˈæTəbˌAs kəntɹˈOlz wˈɛðəɹ pɹˌɑbəbˈɪləTiz, klˈæs kˈɔlz, mˈɑdᵊl fˈIlz, ænd səlˈɛktᵻd fˈiʧəɹz ɑɹ sˈAvd ɔɹ ɹˈɪtn bˈæk tə ðə mˈɛʒəɹmᵊnt pɹˈɑʤˌɛkt." } ] }, { "scene": 9, "speech_start": 89.655, "speech_end": 100.9, "scene_end": 101.42, "duration": 11.765, "text": "Hyperparameter Search is a mini workbench for comparing a focused set of model choices with grouped folds. The results table ranks completed trials and shows their variation.", "speech_text": "hyper-parameter Search is a mini workbench for comparing a focused set of model choices with grouped folds. The results table ranks completed trials and shows their variation.", "phonemes": "hˌIpəɹpəɹˈæməTəɹ sˈɜɹʧ ɪz ɐ mˈɪni wˈɜɹkbˌɛnʧ fɔɹ kəmpˈɛɹɪŋ ɐ fˈOkəst sˈɛt ʌv mˈɑdᵊl ʧˈYsᵻz wɪð ɡɹˈupt fˈOldz. ðə ɹəzˈʌlts tˈAbᵊl ɹˈæŋks kəmplˈiTᵻd tɹˈIᵊlz ænd ʃˈOz ðɛɹ vˌɛɹiˈAʃən.", "authored_hold_after": 0.7, "hold_after": 0.52, "base_speed": 0.94, "speed_multiplier": 1.0, "effective_speed": 0.94, "sentences": [ { "sentence": 1, "speech_start": 89.655, "speech_end": 96.325, "audible_start": 89.755, "audible_end": 96.145, "duration": 6.67, "gap_from_previous": null, "trimmed_lead": 0.155, "trimmed_tail": 0.5, "text": "Hyperparameter Search is a mini workbench for comparing a focused set of model choices with grouped folds.", "speech_text": "hyper-parameter Search is a mini workbench for comparing a focused set of model choices with grouped folds.", "phonemes": "hˌIpəɹpəɹˈæməTəɹ sˈɜɹʧ ɪz ɐ mˈɪni wˈɜɹkbˌɛnʧ fɔɹ kəmpˈɛɹɪŋ ɐ fˈOkəst sˈɛt ʌv mˈɑdᵊl ʧˈYsᵻz wɪð ɡɹˈupt fˈOldz." }, { "sentence": 2, "speech_start": 96.44500000000001, "speech_end": 100.9, "audible_start": 96.545, "audible_end": 100.72, "duration": 4.455, "gap_from_previous": 0.4, "trimmed_lead": 0.17, "trimmed_tail": 0.475, "text": "The results table ranks completed trials and shows their variation.", "speech_text": "The results table ranks completed trials and shows their variation.", "phonemes": "ðə ɹəzˈʌlts tˈAbᵊl ɹˈæŋks kəmplˈiTᵻd tɹˈIᵊlz ænd ʃˈOz ðɛɹ vˌɛɹiˈAʃən." } ] }, { "scene": 10, "speech_start": 101.42, "speech_end": 111.04, "scene_end": 111.56, "duration": 10.14, "text": "Search Settings defines candidate values, trial budget, folds, seed, and ranking metric. Keep the search space small enough to explain and reproduce.", "speech_text": "Search Settings defines candidate values, trial budget, folds, seed, and ranking metric. Keep the search space small enough to explain and reproduce.", "phonemes": "sˈɜɹʧ sˈɛTɪŋz dəfˈInz kˈændədˌAt vˈæljuz, tɹˈIᵊl bˈʌʤət, fˈOldz, sˈid, ænd ɹˈæŋkɪŋ mˈɛtɹɪk. kˈip ðə sˈɜɹʧ spˈAs smˈɔl ɪnˈʌf tʊ ɪksplˈAn ænd ɹˌipɹədˈus.", "authored_hold_after": 0.7, "hold_after": 0.52, "base_speed": 0.94, "speed_multiplier": 1.0, "effective_speed": 0.94, "sentences": [ { "sentence": 1, "speech_start": 101.42, "speech_end": 107.165, "audible_start": 101.52, "audible_end": 106.985, "duration": 5.745, "gap_from_previous": null, "trimmed_lead": 0.155, "trimmed_tail": 0.5, "text": "Search Settings defines candidate values, trial budget, folds, seed, and ranking metric.", "speech_text": "Search Settings defines candidate values, trial budget, folds, seed, and ranking metric.", "phonemes": "sˈɜɹʧ sˈɛTɪŋz dəfˈInz kˈændədˌAt vˈæljuz, tɹˈIᵊl bˈʌʤət, fˈOldz, sˈid, ænd ɹˈæŋkɪŋ mˈɛtɹɪk." }, { "sentence": 2, "speech_start": 107.285, "speech_end": 111.04, "audible_start": 107.385, "audible_end": 110.86, "duration": 3.755, "gap_from_previous": 0.4, "trimmed_lead": 0.16, "trimmed_tail": 0.435, "text": "Keep the search space small enough to explain and reproduce.", "speech_text": "Keep the search space small enough to explain and reproduce.", "phonemes": "kˈip ðə sˈɜɹʧ spˈAs smˈɔl ɪnˈʌf tʊ ɪksplˈAn ænd ɹˌipɹədˈus." } ] }, { "scene": 11, "speech_start": 111.56, "speech_end": 125.87, "scene_end": 126.39, "duration": 14.829999999999998, "text": "Run validates controls, prepares features, applies any plate correction, evaluates the classifier, calculates importance, and saves enabled outputs. Review held-out and per-plate behavior before using predictions biologically.", "speech_text": "Run validates controls, prepares features, applies any plate correction, evaluates the [classifier](/klˈæsəfIəɹ/), calculates importance, and saves enabled outputs. Review held-out and per-plate behavior before using predictions biologically.", "phonemes": "ɹˈʌn vˈælɪdˌAts kəntɹˈOlz, pɹipˈɛɹz fˈiʧəɹz, əplˈIz ˈɛni plˈAt kəɹˈɛkʃən, əvˈæljʊˌAts ðə klˈæsəfIəɹ, kˈælkjəlˌAts ɪmpˈɔɹtᵊns, ænd sˈAvz ɪnˈAbᵊld ˈWtpˌʊts. ɹəvjˈu hˈɛldˌWt ænd pɜɹplˈAt bəhˈAvjəɹ bəfˈɔɹ jˈuzɪŋ pɹidˈɪkʃənz bˌIəlˈɑʤəkᵊli.", "authored_hold_after": 0.7, "hold_after": 0.52, "base_speed": 0.94, "speed_multiplier": 1.0, "effective_speed": 0.94, "sentences": [ { "sentence": 1, "speech_start": 111.56, "speech_end": 120.73, "audible_start": 111.66, "audible_end": 120.55, "duration": 9.17, "gap_from_previous": null, "trimmed_lead": 0.17, "trimmed_tail": 0.51, "text": "Run validates controls, prepares features, applies any plate correction, evaluates the classifier, calculates importance, and saves enabled outputs.", "speech_text": "Run validates controls, prepares features, applies any plate correction, evaluates the [classifier](/klˈæsəfIəɹ/), calculates importance, and saves enabled outputs.", "phonemes": "ɹˈʌn vˈælɪdˌAts kəntɹˈOlz, pɹipˈɛɹz fˈiʧəɹz, əplˈIz ˈɛni plˈAt kəɹˈɛkʃən, əvˈæljʊˌAts ðə klˈæsəfIəɹ, kˈælkjəlˌAts ɪmpˈɔɹtᵊns, ænd sˈAvz ɪnˈAbᵊld ˈWtpˌʊts." }, { "sentence": 2, "speech_start": 120.85, "speech_end": 125.87, "audible_start": 120.95, "audible_end": 125.69, "duration": 5.02, "gap_from_previous": 0.4, "trimmed_lead": 0.165, "trimmed_tail": 0.49, "text": "Review held-out and per-plate behavior before using predictions biologically.", "speech_text": "Review held-out and per-plate behavior before using predictions biologically.", "phonemes": "ɹəvjˈu hˈɛldˌWt ænd pɜɹplˈAt bəhˈAvjəɹ bəfˈɔɹ jˈuzɪŋ pɹidˈɪkʃənz bˌIəlˈɑʤəkᵊli." } ] } ] }