Request Payload
This sub-page helps the integrator to understand various different types of request payload based on the individual task or combination of tasks in that sequence that integrator wants to do.
Request Payload for Individual Task
{
"pipelineTasks": [
{
"taskType": "asr",
"config": {
"language": {
"sourceLanguage": "xx"
},
"serviceId": "xxxxx--ssssss-d-ddd--dddd",
"audioFormat": "wav",
"samplingRate": 16000,
"preProcessors": [
"vad"
],
"postProcessors": [
"itn"
]
}
}
],
"inputData": {
"input": [
{
"source": null
}
],
"audio": [
{
"audioContent": "{{generated_base64_content}}"
}
]
}
}This response contains 2 major parameters listed below and detailed further down the section:
pipelineTasks
inputData
Parameter: pipelineTasks
pipelineTasksType: Array
This parameter takes an array of tasks, in the form of dictionary of taskType and config, that are to be done by the integrator.
In the above example, pipelineTasks takes only one dictionary (line 3-13) because integrator wants to do only ASR.
taskType parameter takes String that takes the value asr
config parameter takes a Dictionary that contains following parameters:
For ASR, language parameter only takes sourceLanguage which accepts ISO-639 Series Code of the language.
Parameter: inputData
inputDatainputData Parameter takes the actual input from the integrator on which the individual task has to be done. It can take the input either via input parameter or audio parameter depending on the task to be done.
Since ASR is done on audio input data, for ASR,
inputparameter is optional, of no use for ASR butaudioparameter is mandatory.
audio parameter takes audioContent parameter which accepts base64 String of the actual audio captured.
Request Payload for Combination of Tasks in specific sequence
{
"pipelineTasks": [
{
"taskType": "asr",
"config": {
"language": {
"sourceLanguage": "xx"
},
"serviceId": "xxxxx--ssssss-d-ddd--dddd",
"audioFormat": "flac",
"samplingRate": 16000
}
},
{
"taskType": "translation",
"config": {
"language": {
"sourceLanguage": "xx",
"targetLanguage": "yy"
},
"serviceId": "xxxxx--ssssss-d-ddd--mfkds"
}
}
],
"inputData": {
"input": [
{
"source": null
}
],
"audio": [
{
"audioContent": "{{generated_base64_content}}"
}
]
}
}Parameter: pipelineTasks
pipelineTasksType: Array
This parameter takes an array of tasks, in the form of dictionary of taskType and config, that are to be done by the integrator.
In the above example, pipelineTasks takes two dictionaries:
Line 3 to 13 i.e.,
ASR DictionaryLine 14 to 23 i.e.,
Translation Dictionary
because integrator wants to do ASR of the input voice followed by Translation of the digital text.
Line Number 7 and Line Number 18 are connected with below understanding. Consider a use-case described below:
Integrator wants to speak in say Hindi language and wants to see the translated output in Marathi. For this to happen, integrator has to:
Convert the Audio integrator has spoken to digital text i.e., ASR of Hindi
Translate this digital Hindi text to Marathi digital text i.e., Translation from Hindi to Marathi
Pre-Processors and Post-Processors within Compute Request
In Automatic Speech Recognition (ASR) systems, preprocessors and postprocessors play a crucial role in refining the audio input and enhancing the textual output, respectively. Below, we provide details on the available preprocessors and postprocessors, along with an example of how to configure them in your request body.
Preprocessors
Voice Activity Detection (VAD)
Syntax:
"preProcessors": ["vad"]Function: VAD allows audio content longer than 30 seconds to be passed and processed. It helps identify voice activity to ensure that only the detected voice activity is processed, reducing the load and improving the efficiency of the ASR system.
Denoiser
Syntax:
"preProcessors": ["denoiser"]Function: Denoiser helps in improving the accuracy of speech recognition by reducing background noise from audio inputs.
Postprocessors
Inverse Text Normalization (ITN)
Syntax:
"postProcessors": ["itn"]Function: ITN converts spoken numbers and dates into their written forms. For example, the ASR would output "two thousand and twenty three" as "2023".
Punctuation
Syntax:
"postProcessors": ["punctuation"]Function: This postprocessor adds punctuations to the ASR output, making the text more readable and closer to natural written language.
Example:
ASR Output: "hello how are you"
Punctuation Output: "Hello, how are you?"
The configuration of preprocessors and postprocessors can be included within the config section of the request body as shown below:
"config": {
"language": {
"sourceLanguage": "xx"
},
"serviceId": "xxxxx--ssssss-d-ddd--dddd",
"audioFormat": "flac",
"samplingRate": 16000,
"preProcessors": ["vad"],
"postProcessors": ["itn", "punctuation"]
}Last updated