Datasets:

DTU54DL
/

common-native-proc

sentence stringlengths 6 166	accent stringlengths 15 147	input_features sequence	labels sequence
Why does Melissandre look like she wants to consume Jon Snow on the ride up the wall?	United States English	[[-0.9590109586715698,-0.9590109586715698,-0.9590109586715698,-0.9590109586715698,-0.959010958671569(...TRUNCATED)	[50258,50259,50359,50363,8429,775,7375,891,474,265,574,411,750,2738,220,1353,14732,7745,14827,322,22(...TRUNCATED)
A young girl dressed all in pink is standing on a fence and looking at a horse	United States English	[[-0.5811513662338257,-0.5811513662338257,-0.5811513662338257,-0.5811513662338257,-0.581151366233825(...TRUNCATED)	[50258,50259,50359,50363,32,2037,2013,12386,439,294,7022,307,4877,322,257,15422,293,1237,412,257,683(...TRUNCATED)
In an undertone, or whisper	United States English	[[-1.0612664222717285,-1.0612664222717285,-1.0612664222717285,-1.0612664222717285,-1.061266422271728(...TRUNCATED)	[ 50258, 50259, 50359, 50363, 4575, 364, 15564, 546, 11, 420, 26018, 50257 ]
A man wearing black pants and no shoes appears to float in a laundry room.	United States English	[[-0.9388316869735718,-0.9388316869735718,-0.9388316869735718,-0.8921617269515991,-0.798167824745178(...TRUNCATED)	[50258,50259,50359,50363,32,587,4769,2211,10082,293,572,6654,7038,220,1353,15706,294,257,19811,1808,(...TRUNCATED)
A female athlete is in the process of completing a high jump.	United States English	[[-1.1746602058410645,-1.1746602058410645,-1.1746602058410645,-0.6188827753067017,-0.731233119964599(...TRUNCATED)	[ 50258, 50259, 50359, 50363, 32, 6556, 18002, 307, 294, 220, 3322, 1399, 295, 19472, 257, 1090, 3012, 13, 50257 ]
A woman is talking on the phone while standing next to a dog.	United States English	[[-1.0835216045379639,-1.0835216045379639,-1.0835216045379639,-0.83793044090271,-0.6801940202713013,(...TRUNCATED)	[50258,50259,50359,50363,32,3059,307,220,29302,278,322,220,3322,2593,1339,4877,958,220,1353,257,3000(...TRUNCATED)
A man is cooking outside on a grill.	United States English	[[-1.1721041202545166,-1.1721041202545166,-1.1721041202545166,-0.7762984037399292,-0.708817481994628(...TRUNCATED)	[ 50258, 50259, 50359, 50363, 32, 587, 307, 6361, 2380, 322, 257, 16492, 13, 50257 ]
A woman and a little girl pose for a picture with a llama atop a hillside.	United States English	[[-0.8943901062011719,-0.8943901062011719,-0.8943901062011719,-0.7599804401397705,-0.770349383354187(...TRUNCATED)	[50258,50259,50359,50363,32,3059,293,257,707,2013,10774,337,257,3036,365,257,23272,412,404,257,10997(...TRUNCATED)
Working from home has both drawbacks and advantages.	England English	[[-0.8952903747558594,-0.8952903747558594,-0.8952903747558594,-0.8952903747558594,-0.895290374755859(...TRUNCATED)	[ 50258, 50259, 50359, 50363, 28846, 278, 490, 1280, 575, 1293, 2642, 17758, 293, 14906, 13, 50257 ]
A construction worker is talking on the phone in a train tunnel.	England English	[[-0.8499531745910645,-0.8499531745910645,-0.8499531745910645,-0.8499531745910645,-0.849953174591064(...TRUNCATED)	[50258,50259,50359,50363,32,6435,11346,307,220,29302,278,322,220,3322,2593,294,257,220,83,7146,220,8(...TRUNCATED)

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YAML Metadata Warning: The task_ids "token-classification-other-acronym-identification" is not in the official list: acceptability-classification, entity-linking-classification, fact-checking, intent-classification, language-identification, multi-class-classification, multi-label-classification, multi-input-text-classification, natural-language-inference, semantic-similarity-classification, sentiment-classification, topic-classification, semantic-similarity-scoring, sentiment-scoring, sentiment-analysis, hate-speech-detection, text-scoring, named-entity-recognition, part-of-speech, parsing, lemmatization, word-sense-disambiguation, coreference-resolution, extractive-qa, open-domain-qa, closed-domain-qa, news-articles-summarization, news-articles-headline-generation, dialogue-modeling, dialogue-generation, conversational, language-modeling, text-simplification, explanation-generation, abstractive-qa, open-domain-abstractive-qa, closed-domain-qa, open-book-qa, closed-book-qa, slot-filling, masked-language-modeling, keyword-spotting, speaker-identification, audio-intent-classification, audio-emotion-recognition, audio-language-identification, multi-label-image-classification, multi-class-image-classification, face-detection, vehicle-detection, instance-segmentation, semantic-segmentation, panoptic-segmentation, image-captioning, image-inpainting, image-colorization, super-resolution, grasping, task-planning, tabular-multi-class-classification, tabular-multi-label-classification, tabular-single-column-regression, rdf-to-text, multiple-choice-qa, multiple-choice-coreference-resolution, document-retrieval, utterance-retrieval, entity-linking-retrieval, fact-checking-retrieval, univariate-time-series-forecasting, multivariate-time-series-forecasting, visual-question-answering, document-question-answering