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Audio transcription — Step-by-step instructions

The challenge

We have a set of audio recordings and we need to obtain a transcription of each recording. We ask performers to listen to the recordings and type what they hear. Here’s what it might look like:

Video: 7 basic steps to run a project
Create
a project
Create
an exam pool
Create
a task pool
Upload a file
with data
Create
control tasks
Launch
the pool
Get the
results

Create a project

Interface code

{
  "vars": {
    "validString": {
      "type": "condition.all",
      "conditions": [
        {
          "type": "condition.schema",
          "schema": {
            "type": "string",
            "pattern": "^[a-zA-Z\\*\\s]{1,}$"
          }
        }
      ],
      "hint": "Use only lowercase letters and spaces"
    }
  },
  "view": {
    "type": "view.list",
    "items": [
      {
        "type": "view.audio",
        "validation": {
          "type": "condition.played-fully",
          "hint": "You didn't listen to the recording"
        },
        "url": {
          "type": "data.input",
          "path": "audio"
        }
      },
      {
        "type": "view.text"
      },
      {
        "type": "field.text",
        "label": "Transcription text",
        "data": {
          "type": "data.output",
          "path": "result_unformat"
        },
        "validation": {
          "$ref": "vars.validString"
        }
      }
    ]
  },
  "plugins": [
    {
      "type": "plugin.trigger",
      "onChangeOf": {
        "type": "data.output",
        "path": "result_unformat"
      },
      "action": {
        "type": "action.set",
        "data": {
          "type": "data.output",
          "path": "result"
        },
        "payload": {
          "type": "helper.text-transform",
          "transformation": "lowercase",
          "data": {
            "type": "helper.replace",
            "data": {
              "type": "data.output",
              "path": "result_unformat"
            },
            "find": "/(\\s{2,})/",
            "replace": " "
          }
        }
      }
    },
    {
      "type": "plugin.toloka",
      "layout": {
        "kind": "scroll",
        "taskWidth": 900
      }
    },
    {
      "type": "plugin.hotkeys",
      "q": {
        "type": "action.play-pause",
        "view": {
          "$ref": "view.items.0"
        }
      }
    }
  ]
}

Create an exam pool

Exam dataset
Prepare a TSV file with tasks as shown in our example.
Origin
Valentini-Botinhao, Cassia. (2017). Noisy speech database for training speech enhancement algorithms and TTS models, 2016 [sound]. University of Edinburgh. School of Informatics. Centre for Speech Technology Research (CSTR). https://doi.org/10.7488/ds/2117.
License: CC BY 4.0

Create a task pool

Upload a file with data

Dataset
Prepare a TSV file with tasks as shown in our example.
You can also upload a file that already contains golden sets: example.
Origin
Valentini-Botinhao, Cassia. (2017). Noisy speech database for training speech enhancement algorithms and TTS models, 2016 [sound]. University of Edinburgh. School of Informatics. Centre for Speech Technology Research (CSTR). https://doi.org/10.7488/ds/2117.
License: CC BY 4.0

Create control tasks

Dataset with control tasks
You can upload a file that already contains golden sets: example.
Origin
Valentini-Botinhao, Cassia. (2017). Noisy speech database for training speech enhancement algorithms and TTS models, 2016 [sound]. University of Edinburgh. School of Informatics. Centre for Speech Technology Research (CSTR). https://doi.org/10.7488/ds/2117.
License: CC BY 4.0

Launch the pool

Get the results

Application for corporate training
We are offering corporate training to help you solve existing challenges and develop
an internal team of Crowd Science Architects (CSA).
Mon Oct 04 2021 12:22:18 GMT+0300 (Moscow Standard Time)