Speech-to-Text API
Text-to-Speech API
Audio Intelligence API
SpeechFlow, MyGPT, Bing AI Extension, SpeechEvalPro, Deepgram Voice AI, Music.AI, SteosVoice, ExpenSee, AssemblyAI, Bland AI are the best paid / free voice recognition api tools.
Voice recognition API, also known as speech recognition API, is a technology that enables software applications to convert spoken words into text. It leverages artificial intelligence and machine learning algorithms to accurately transcribe human speech in real-time or from pre-recorded audio. Voice recognition APIs have become increasingly popular in recent years, with applications ranging from virtual assistants and voice-controlled devices to automated transcription services and accessibility tools.
Core Features
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How to use
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Deepgram Voice AI | Speech-to-Text API | Integrate Deepgram Voice AI APIs into your applications by following the documentation and tutorials provided. You can transcribe speech with unmatched accuracy, speed, and cost using the Speech-to-Text API. For real-time AI agents, utilize the Text-to-Speech API to generate human-like speech. The Audio Intelligence API, powered by AI language models, enhances audio understanding. | |
AssemblyAI | Transcribe audio files, video files, and live speech into text | To use AssemblyAI, developers can integrate the API into their applications or services. They can convert audio files, video files, and live speech into text by making API requests. The API provides features like speaker labels, word-level timestamps, profanity filtering, custom vocabulary, and more. Developers can also leverage the Audio Intelligence models and the LeMUR framework to build AI-powered applications with voice data. | |
Bland AI | Automated task processing |
Basic $9.99/month Includes basic features and limited usage.
| To use Bland AI, simply sign up for an account on the website and follow the onboarding process. Once onboarded, you can integrate Bland AI into your existing systems and workflows. |
Label Studio | Flexible data labeling for all data types | To use Label Studio, you can follow these steps: 1. Install the Label Studio package through pip, brew, or clone the repository from GitHub. 2. Launch Label Studio using the installed package or Docker. 3. Import your data into Label Studio. 4. Choose the data type (images, audio, text, time series, multi-domain, or video) and select the specific labeling task (e.g., image classification, object detection, audio transcription). 5. Start labeling your data using customizable tags and templates. 6. Connect to your ML/AI pipeline and use webhooks, Python SDK, or API for authentication, project management, and model predictions. 7. Explore and manage your dataset in the Data Manager with advanced filters. 8. Support multiple projects, use cases, and users within the Label Studio platform. | |
Music.AI | Wide range of state-of-the-art AI models for audio-driven AI products | To use Music.AI, companies and developers can leverage the Audio Intelligence Platform™, which provides state-of-the-art Complementary AI™ models tailored to empower businesses and developers. The platform offers a user-friendly interface with drag-and-drop functionality, API integration, native client support, and comprehensive SDKs. It also ensures the privacy and security of data, allowing users to train their own models. | |
SteosVoice | Ultra-realistic speech synthesis | To use SteosVoice, simply sign in or register an account on the platform. Once logged in, you can access over 150 voices and utilize them in various ways. You can create unique content by dubbing videos, adding voice messages for your patrons, or even localizing your YouTube channel. Additionally, SteosVoice can be used for audio books, podcasts, and even as a Telegram Bot. The platform also offers monetization opportunities, allowing you to make money from your voice. | |
SpeechFlow | SpeechFlow provides high accuracy in transcribing speech to text in 14 languages. | To use SpeechFlow, you can either upload an audio file or provide a YouTube link. The API will process, interpret, and understand the speech signal to generate the corresponding text. You can choose from 14 supported languages, including English, French, German, Japanese, Korean, Russian, and Spanish. The API is easy to deploy and scale, with options for both cloud and on-prem deployment. Simply integrate the provided code snippet in your application to start transcribing speech to text. | |
MyGPT | The core features of MyGPT include: - Access to GPT-4 for powerful and creative ideation. - State-of-the-art voice recognition with Whisper for an intuitive user experience. - AI neural-based TTS (text-to-speech) for lifelike and customizable bot voices. - Customizable bots suited for personal needs and business growth guidance. - Open source tools available on GitHub for workflow customization. - API with limitless possibilities for personalization and clever hacks. - Dedicated support and assistance for glitch fixing or feature requests. |
subscription
| To use MyGPT, follow these steps: 1. Register an account on the website. 2. Choose a subscription plan based on your needs. 3. Access the platform and activate the @mygptlinkbot in Telegram. 4. Design and customize your own bots using the intuitive interface. 5. Use the provided API to personalize and enhance your bots further. 6. Enjoy the prompt and lively interactions with your customized bots. |
SpeechEvalPro | The core features of SpeechEvalPro include:- Pronunciation assessment and scoring API- Voice evaluation and speech recognition- Multi-dimensional evaluation for Chinese and English pronunciation- Support for various question types and languages- Real data labeling and model training for accuracy- Fluency assessment for speed and pauses- Integrity assessment for missing or repeated words- Specify phonetic pronunciation in Chinese evaluation- Simple access via HTTP and WebSocket protocols |
free_trial $0
| To use SpeechEvalPro, you need to sign up for a free trial or choose a suitable pricing plan. Once you have access, you can integrate the API into your learning product or application by making HTTP or WebSocket requests. The API accepts audio files in recommended formats and supports various question types, such as phoneme, word, sentence, and chapter modes. You can refer to the documentation for detailed instructions and guidelines on API usage. |
ClearCypherAI | Text-to-Audio (T2A) | To use ClearCypherAI, you can request a demo to explore their capabilities. They offer products such as automated speech recognition (ASR) for converting audio to text, voice synthesis for converting text to audio, and fine-tuned GPT models for text-to-text tasks. You can also benefit from their voiceprint and synthesis feature, threat assessment platform, in-house AI research, and access to built natural language datasets. They provide full customer support and services, including building custom AI platforms and datasets, API hosting, feature customization, and more. Additionally, ClearCypherAI offers AI solutions that can be deployed in air gapped environments. |
AI Podcast Assistant
Large Language Models (LLMs)
Captions or Subtitle
Transcription
Transcriber
AI Audio Enhancer
Recording
Speech-to-Text
Voice & Audio Editing
AI Speech Recognition
AI Content Generator
AI Noise Cancellation
AI Chatbot
Writing Assistants
AI Voice Assistants
Customer service: Transcribing customer calls for quality assurance and training purposes.
Healthcare: Documenting patient encounters and generating medical reports through dictation.
Legal: Transcribing court proceedings, depositions, and legal documents for record-keeping and analysis.
Education: Providing real-time captions for online courses and transcribing educational content for students.
Media and entertainment: Subtitling videos, transcribing podcasts, and generating closed captions for live events.
Users generally praise voice recognition APIs for their accuracy, ease of integration, and time-saving capabilities. Many appreciate the ability to transcribe speech in real-time and the support for multiple languages. However, some users note that accuracy can be affected by factors such as background noise, accents, and domain-specific terminology. Users also emphasize the importance of choosing a provider with strong security and privacy measures. Overall, voice recognition APIs are seen as valuable tools for a wide range of applications, from accessibility and user experience to productivity and cost savings.
A user dictates a text message or email to their smartphone, which transcribes the speech and sends the message.
A user asks a virtual assistant to set a reminder or play a song, and the assistant interprets the voice command.
A user speaks into a smart home device to control lights, thermostats, or other connected appliances.
A user records a lecture or meeting, and the voice recognition API automatically transcribes the audio for later reference.
To use a voice recognition API, developers typically need to follow these steps: 1. Choose a voice recognition API provider and sign up for an API key. 2. Integrate the API into their software application using the provided SDK or REST endpoints. 3. Pass audio data to the API, either in real-time or as pre-recorded files. 4. Receive the transcribed text from the API and process it according to the application's requirements. 5. Optionally, train the API with domain-specific terminology or custom language models to improve accuracy.
Improved accessibility: Enables voice-based interaction for users with disabilities or limited mobility.
Enhanced user experience: Provides a natural and intuitive way for users to interact with applications.
Increased productivity: Allows for hands-free operation and faster input compared to typing.
Cost savings: Automates transcription tasks, reducing the need for manual labor.
Multilingual support: Facilitates communication and collaboration across different languages.