Datasets:
merged dict |
|---|
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.2576,
"emotion_score": 0.48715,
"humanity_score": 0.18916000000000002
},
"csv_matched": false,
"embeddings": {
... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.433749999999999,
"emotion_score": 0.9496,
"humanity_score": 0.25972
},
"csv_matched": false,
"embeddings": {
... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.5499,
"emotion_score": 0.5014500000000001,
"humanity_score": 0.38692000000000004
},
"csv_matched": false,
"embe... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.43015000000000003,
"emotion_score": 0.40190000000000003,
"humanity_score": 0.27624000000000004
},
"csv_matched": fa... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.43155000000000004,
"emotion_score": 0.376,
"humanity_score": 0.26616
},
"csv_matched": false,
"embeddings": {
... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.33975000000000005,
"emotion_score": 0.2426,
"humanity_score": 0.15968000000000002
},
"csv_matched": false,
"emb... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 14.60455,
"emotion_score": 0.2894,
"humanity_score": 13.53106
},
"csv_matched": false,
"embeddings": {
"emb... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.27325000000000005,
"emotion_score": 0.24445000000000003,
"humanity_score": 1.321019999999999
},
"csv_matched": fals... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.24105000000000001,
"emotion_score": 0.33235000000000003,
"humanity_score": 0.10796000000000001
},
"csv_matched": fa... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.2641,
"emotion_score": 0.4027,
"humanity_score": 1.48502
},
"csv_matched": false,
"embeddings": {
"embedd... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.55715,
"emotion_score": 0.623699999999999,
"humanity_score": 0.9865600000000001
},
"csv_matched": false,
"embed... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.45830000000000004,
"emotion_score": 0.15925,
"humanity_score": 0.25784
},
"csv_matched": false,
"embeddings": {... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.194699999999999,
"emotion_score": 0.8457500000000001,
"humanity_score": 2.028019999999999
},
"csv_matched": false,
... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.4898,
"emotion_score": 0.26730000000000004,
"humanity_score": 0.8121
},
"csv_matched": false,
"embeddings": {
... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.5165000000000001,
"emotion_score": 0.67395,
"humanity_score": 0.6814
},
"csv_matched": false,
"embeddings": {
... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.287649999999999,
"emotion_score": 0.5725,
"humanity_score": 0.15288000000000002
},
"csv_matched": false,
"embed... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.35165,
"emotion_score": 0.19865000000000002,
"humanity_score": 0.20692000000000002
},
"csv_matched": false,
"em... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.36495000000000005,
"emotion_score": 0.41485000000000005,
"humanity_score": 0.20600000000000002
},
"csv_matched": fa... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.5939,
"emotion_score": 0.5029,
"humanity_score": 0.660099999999999
},
"csv_matched": false,
"embeddings": {
... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.279549999999999,
"emotion_score": 0.8398500000000001,
"humanity_score": 0.17524
},
"csv_matched": false,
"embed... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.45520000000000005,
"emotion_score": 0.81315,
"humanity_score": 0.33562000000000003
},
"csv_matched": false,
"em... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.48555000000000004,
"emotion_score": 0.17085,
"humanity_score": 0.28296000000000004
},
"csv_matched": false,
"em... |
{
"features_extracted": {
"cadence_detection": {
"cadence_rate": 0,
"cadences": [],
"count": 0
},
"cross_analysis_scores": {
"complexity_score": 0.4939,
"emotion_score": 0.3327,
"humanity_score": 0.30364
},
"csv_matched": false,
"embeddings": {
"embedd... |
YAML Metadata Warning:The task_categories "music-transcription" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
YAML Metadata Warning:The task_categories "generative-modeling" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
YAML Metadata Warning:The task_categories "audio-processing" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
YAML Metadata Warning:The task_categories "machine-learning" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
Lakh MIDI Dataset — Fully Cleaned & Structured JSON (44,129 files)
This dataset is a fully cleaned and normalized version of the Lakh MIDI Dataset.
Each MIDI file has been parsed, validated, and converted into a consistent JSON structure with detailed musical metadata.
✔ 44,129 cleaned JSON files
✔ instrument programs
✔ notes, durations, velocities
✔ tempo curves
✔ key signatures
✔ time signatures
✔ tracks & channels
✔ structural markers
✔ file-level metadata
✔ consistent schema across all files
Suitable for:
- Music AI
- symbolic modeling
- generative models
- audio-to-symbolic learning
- embeddings
- piano transcription
- MIR research
- supervised ML datasets
- music information retrieval
License: Same as original Lakh dataset (public research dataset, metadata extracted legally).
All JSON files are derived from open-source MIDI data.
For commercial or large-scale dataset cleaning services:
— Zeronex
- Downloads last month
- 27