API Docs
Speech Text Extraction
POST/api/ai/speech-textSpeech Extraction AI
Extract Speech from Audio in Multiple Spoken Languages
Introducing SpeechAI, an extraordinary speech recognition model that will revolutionize the way you work with audio data. With an extensive training of 850,000 hours of diverse audio, SpeechAI achieves near human-level performance and unwavering reliability.
No longer will you be limited by the variety of data. SpeechAI effortlessly handles different audio inputs, providing accurate transcriptions and enabling you to explore new possibilities in your applications.
In this developer documentation, you'll find all the information you need to integrate SpeechAI into your projects. Experience the seamless conversion of spoken words into written text with unparalleled precision. Let SpeechAI amplify the power of your applications and transform the way you interact with audio.
How does it work?
SpeechAI is a cutting-edge neural network designed for speech recognition, based on a renowned research paper published by Google Brain in 2020. It builds upon the widely adopted Transformer architecture, known for its parallel processing capability and effective utilization of attention mechanisms. By incorporating convolutional layers into the Transformer architecture, SpeechAI excels at capturing both local and global dependencies in audio data, all while maintaining a compact neural network design that can be seamlessly deployed on clients.
Our primary objective with SpeechAI was to develop a production-ready speech recognition model that could be effortlessly deployed at an extensive scale. We sought to leverage the remarkable modeling capabilities of the original Conformer architecture to achieve this goal. The integration of Conformer's exceptional features into SpeechAI ensures superior performance and enables users to harness its power for a wide range of applications.
With SpeechAI, you can experience the fusion of advanced neural network architecture and state-of-the-art speech recognition techniques. Say goodbye to traditional limitations as you unleash the potential of SpeechAI in your projects, taking speech recognition to unprecedented heights.
Use Cases
Transcription: Speech to text AI can be used to automatically transcribe audio or video recordings into text format. This can be useful for businesses or individuals who need to transcribe interviews, meetings, or other audio content.
Closed captioning: Speech to text AI can be used to generate closed captions for videos, making them accessible to people with hearing impairments. This is important for ensuring that content is accessible to everyone, regardless of their abilities.
Voice search: Speech to text AI can be used to power voice search functionality in search engines or other applications. This allows users to search for information using their voice, making the process more natural and intuitive.
Customer service: Speech to text AI can be used to transcribe customer service calls, allowing businesses to analyze the conversations and identify areas for improvement. It can also be used to generate transcripts of customer service chats or emails.
Language learning: Speech to text AI can be used to transcribe and analyze language conversations, helping language learners to improve their listening and comprehension skills. It can also be used to generate transcripts of language lessons or podcasts.
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Request samples
Responses
{
"data": {
"text": "The model is called bark like Clifford the big red dog, or. Or bark as in tree bark.",
"speaker_labels": [
{
"speaker": "A",
"text": "The model is called bark like Clifford the big red dog, or. Or bark as in tree bark."
}
],
"timestamps": [
{
"word": "The",
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"duration": 136
},
{
"word": "model",
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"end_time": 1679,
"duration": 336
},
{
"word": "is",
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"end_time": 1983,
"duration": 256
},
{
"word": "called",
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"duration": 648
},
{
"word": "bark",
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"end_time": 3635,
"duration": 764
},
{
"word": "like",
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"end_time": 4735,
"duration": 360
},
{
"word": "Clifford",
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"end_time": 5095,
"duration": 320
},
{
"word": "the",
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"duration": 128
},
{
"word": "big",
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"end_time": 5431,
"duration": 152
},
{
"word": "red",
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"end_time": 5655,
"duration": 192
},
{
"word": "dog,",
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"end_time": 6275,
"duration": 580
},
{
"word": "or.",
"start_time": 6615,
"end_time": 7355,
"duration": 740
},
{
"word": "Or",
"start_time": 8775,
"end_time": 9515,
"duration": 740
},
{
"word": "bark",
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"end_time": 10895,
"duration": 400
},
{
"word": "as",
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"end_time": 11063,
"duration": 128
},
{
"word": "in",
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"end_time": 11231,
"duration": 152
},
{
"word": "tree",
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"end_time": 11455,
"duration": 192
},
{
"word": "bark.",
"start_time": 11495,
"end_time": 11615,
"duration": 120
}
]
},
"processingTime": 7652.61689,
"processingId": "a3013205-5f7a-4e44-aa6f-01ce0801418f",
"processingCount": 18
}