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import type { TaskDataCustom } from "../Types";
const taskData: TaskDataCustom = {
datasets: [
{
description: "18,000 hours of multilingual audio-text dataset in 108 languages.",
id: "mozilla-foundation/common_voice_13_0",
},
{
description: "An English dataset with 1,000 hours of data.",
id: "librispeech_asr",
},
{
description: "High quality, multi-speaker audio data and their transcriptions in various languages.",
id: "openslr",
},
],
demo: {
inputs: [
{
filename: "input.flac",
type: "audio",
},
],
outputs: [
{
/// GOING ALONG SLUSHY COUNTRY ROADS AND SPEAKING TO DAMP AUDIENCES I
label: "Transcript",
content: "Going along slushy country roads and speaking to damp audiences in...",
type: "text",
},
],
},
metrics: [
{
description: "",
id: "wer",
},
{
description: "",
id: "cer",
},
],
models: [
{
description: "A powerful ASR model by OpenAI.",
id: "openai/whisper-large-v2",
},
{
description: "A good generic ASR model by MetaAI.",
id: "facebook/wav2vec2-base-960h",
},
{
description: "An end-to-end model that performs ASR and Speech Translation by MetaAI.",
id: "facebook/s2t-small-mustc-en-fr-st",
},
],
spaces: [
{
description: "A powerful general-purpose speech recognition application.",
id: "openai/whisper",
},
{
description: "Fastest speech recognition application.",
id: "sanchit-gandhi/whisper-jax",
},
{
description: "An application that transcribes speeches in YouTube videos.",
id: "jeffistyping/Youtube-Whisperer",
},
],
summary:
"Automatic Speech Recognition (ASR), also known as Speech to Text (STT), is the task of transcribing a given audio to text. It has many applications, such as voice user interfaces.",
widgetModels: ["openai/whisper-large-v2"],
youtubeId: "TksaY_FDgnk",
};
export default taskData;