Compare
LibriSpeech vs COCO 2017
Side-by-side comparison of LibriSpeech (Dataset) and COCO 2017 (Dataset).
Live Data← All Comparisons
80.2
Composite Score
LibriSpeech
Dataset · OpenSLR / Johns Hopkins University
82.5
Composite Score
COCO 2017
Dataset · Microsoft
Overall Winner
COCO 2017
LibriSpeech wins 0 of 6 categories · COCO 2017 wins 5 of 6 categories
Score Comparison
LibriSpeechvsCOCO 2017
Composite
80.2:82.5
Adoption
95:97
Quality
92:96
Freshness
55:65
Citations
95:98
Engagement
0:0
Details
FieldLibriSpeechCOCO 2017
TypeDatasetDataset
ProviderOpenSLR / Johns Hopkins UniversityMicrosoft
Version20152017
Categoryspeech-audiocomputer-vision
Pricingfreefree
LicenseCC-BY-4.0CC-BY-4.0
DescriptionLibriSpeech is a corpus of approximately 1,000 hours of 16kHz read English speech derived from LibriVox audiobooks, split into clean and other subsets of 100h and 360h for training, with dedicated development and test sets. It has become the de facto standard benchmark for English ASR systems.Microsoft COCO (Common Objects in Context) 2017 provides 118K training images with 860K object instances annotated with bounding boxes, segmentation masks, keypoints, and captions across 80 object categories. It remains the primary benchmark for object detection and instance segmentation research.
Capabilities
Only LibriSpeech
speech-recognitionspeech-synthesisspeaker-identification
Shared
None
Only COCO 2017
object-detectioninstance-segmentationkeypoint-detectionimage-captioning
Integrations
Only LibriSpeech
HuggingFace DatasetstorchaudioESPnet
Shared
None
Only COCO 2017
PyTorchTensorFlowDetectron2MMDetection
Tags
Only LibriSpeech
automatic-speech-recognitionASRenglishaudiobooks
Shared
benchmark
Only COCO 2017
object-detectionsegmentationkeypointscaptions
Use Cases
LibriSpeech
- ▸model training
- ▸benchmark
- ▸speech research
COCO 2017
- ▸model training
- ▸benchmark
- ▸computer vision research
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