AI-Driven Voice Assistant for Wearable and Placed Item
Budget: £10 – £15 GBP
I'm looking for a skilled team to develop an AI-based voice assistant integrated into a wearable device. The primary function of this assistant will be serving as a personal assistant, similar to Siri or Google Assistant, but with a unique twist and capabilities tailored for our specific device.
We are seeking a highly skilled team of developers to create an advanced voice assistant product that integrates ChatGPT with live audio responses. Users will engage in real-time conversation with the assistant, activated by a wake word, just like modern voice assistants (e.g., Alexa, Siri). The product should handle speech recognition, natural language processing, and speech synthesis, creating a fluid, real-time conversational experience.
Key Features:
Wake word detection to activate the assistant.
Two-way conversational interaction (users speak, AI responds).
Integration with ChatGPT for generating conversational responses.
Real-time audio responses with minimal latency.
Customizable voice and conversation settings.
Responsibilities:
The team will be responsible for:
End-to-End Product Development:
Designing, developing, and deploying the voice assistant from concept to launch.
Ensuring smooth real-time voice-to-voice interaction using AI and other services.
Wake Word Detection:
Implementing wake word detection (e.g., Snowboy or Picovoice).
Customizing the AI name trigger and optimizing for real-time performance.
Speech Recognition (Speech-to-Text):
Integrating with a Speech-to-Text engine (e.g., Google Cloud, Microsoft Azure, or DeepSpeech).
Capturing user speech after the wake word and converting it into text for processing.
Natural Language Processing (ChatGPT Integration):
Setting up and configuring the OpenAI GPT-4 API for text-based conversations.
Ensuring smooth back-and-forth conversations between users and the AI.
Text-to-Speech Integration:
Converting AI-generated text back into speech using Text-to-Speech (e.g., Google Cloud TTS, Amazon Polly).
Customizing the voice (speed, tone, and naturalness) for a human-like experience.
Real-Time Audio Streaming:
Ensuring low-latency streaming for both input (speech recognition) and output (speech synthesis).
Implementing real-time audio playback using low-latency protocols (e.g., WebRTC).
User Interface (UI/UX) Design:
Developing a clean and intuitive interface for the product (for mobile, desktop, or device).
Implementing visual cues (e.g., voice listening indicators) and audio controls.
Backend and Infrastructure:
Building and managing a cloud-based backend to handle real-time speech processing, AI requests, and response generation.
Setting up server infrastructure (AWS, Google Cloud, or Azure) for speech-to-text, ChatGPT, and text-to-speech handling.
Testing and Optimization:
Thoroughly testing the assistant for performance, accuracy, and low latency.
Optimizing for various accents, languages, and environmental conditions.
Skills and Qualifications:
Required Expertise:
Wake Word Detection: Experience with wake word detection systems like Snowboy or Picovoice.
Speech Recognition: Proficiency in integrating cloud-based speech recognition APIs (Google Cloud, Azure) or open-source alternatives (DeepSpeech).
Natural Language Processing: Experience working with the OpenAI GPT API, including fine-tuning for conversational AI.
Text-to-Speech: Experience integrating TTS engines such as Google Cloud TTS or Amazon Polly.
Audio Processing: Experience with real-time audio streaming and playback (using WebRTC or similar technologies).
Backend Development: Strong experience in cloud infrastructure (AWS, Azure, Google Cloud) and handling real-time requests efficiently.
Frontend/UI Development: Proficiency in building user-friendly interfaces for mobile or desktop platforms (Flutter, React Native, Electron).
System Integration: Ability to integrate multiple APIs, libraries, and real-time data flow.
Preferred Skills:
Real-Time Application Development: Experience developing real-time or low-latency applications.
Mobile Development: Experience building mobile apps with conversational AI functionality.
Device Integration (Optional): Experience with hardware integration (e.g., smart speaker systems).
Deliverables:
A fully functional voice assistant capable of real-time, two-way conversations.
Seamless integration with ChatGPT for natural language responses.
Optimized wake word detection with minimal false activations.
High-quality speech recognition and natural-sounding TTS.
User-friendly interface (mobile/desktop or standalone device).
Thorough documentation, including setup and maintenance guidelines.
Timeline:
Estimated project completion: [Insert your preferred timeline, e.g., 3-6 months].
Milestone-based payment structure.
Budget:
TBC
Interested candidates or teams, please provide:
Portfolio of similar projects you’ve worked on.
Breakdown of your approach to tackling this project.
Estimated project timeline and team composition.
Budget proposal and payment structure.
We are looking for highly skilled professionals who are passionate about AI-driven technology and can deliver a product that matches today’s top voice assistants in terms of performance and quality.
We are seeking a highly skilled team of developers to create an advanced voice assistant product that integrates ChatGPT with live audio responses. Users will engage in real-time conversation with the assistant, activated by a wake word, just like modern voice assistants (e.g., Alexa, Siri). The product should handle speech recognition, natural language processing, and speech synthesis, creating a fluid, real-time conversational experience.
Key Features:
Wake word detection to activate the assistant.
Two-way conversational interaction (users speak, AI responds).
Integration with ChatGPT for generating conversational responses.
Real-time audio responses with minimal latency.
Customizable voice and conversation settings.
Responsibilities:
The team will be responsible for:
End-to-End Product Development:
Designing, developing, and deploying the voice assistant from concept to launch.
Ensuring smooth real-time voice-to-voice interaction using AI and other services.
Wake Word Detection:
Implementing wake word detection (e.g., Snowboy or Picovoice).
Customizing the AI name trigger and optimizing for real-time performance.
Speech Recognition (Speech-to-Text):
Integrating with a Speech-to-Text engine (e.g., Google Cloud, Microsoft Azure, or DeepSpeech).
Capturing user speech after the wake word and converting it into text for processing.
Natural Language Processing (ChatGPT Integration):
Setting up and configuring the OpenAI GPT-4 API for text-based conversations.
Ensuring smooth back-and-forth conversations between users and the AI.
Text-to-Speech Integration:
Converting AI-generated text back into speech using Text-to-Speech (e.g., Google Cloud TTS, Amazon Polly).
Customizing the voice (speed, tone, and naturalness) for a human-like experience.
Real-Time Audio Streaming:
Ensuring low-latency streaming for both input (speech recognition) and output (speech synthesis).
Implementing real-time audio playback using low-latency protocols (e.g., WebRTC).
User Interface (UI/UX) Design:
Developing a clean and intuitive interface for the product (for mobile, desktop, or device).
Implementing visual cues (e.g., voice listening indicators) and audio controls.
Backend and Infrastructure:
Building and managing a cloud-based backend to handle real-time speech processing, AI requests, and response generation.
Setting up server infrastructure (AWS, Google Cloud, or Azure) for speech-to-text, ChatGPT, and text-to-speech handling.
Testing and Optimization:
Thoroughly testing the assistant for performance, accuracy, and low latency.
Optimizing for various accents, languages, and environmental conditions.
Skills and Qualifications:
Required Expertise:
Wake Word Detection: Experience with wake word detection systems like Snowboy or Picovoice.
Speech Recognition: Proficiency in integrating cloud-based speech recognition APIs (Google Cloud, Azure) or open-source alternatives (DeepSpeech).
Natural Language Processing: Experience working with the OpenAI GPT API, including fine-tuning for conversational AI.
Text-to-Speech: Experience integrating TTS engines such as Google Cloud TTS or Amazon Polly.
Audio Processing: Experience with real-time audio streaming and playback (using WebRTC or similar technologies).
Backend Development: Strong experience in cloud infrastructure (AWS, Azure, Google Cloud) and handling real-time requests efficiently.
Frontend/UI Development: Proficiency in building user-friendly interfaces for mobile or desktop platforms (Flutter, React Native, Electron).
System Integration: Ability to integrate multiple APIs, libraries, and real-time data flow.
Preferred Skills:
Real-Time Application Development: Experience developing real-time or low-latency applications.
Mobile Development: Experience building mobile apps with conversational AI functionality.
Device Integration (Optional): Experience with hardware integration (e.g., smart speaker systems).
Deliverables:
A fully functional voice assistant capable of real-time, two-way conversations.
Seamless integration with ChatGPT for natural language responses.
Optimized wake word detection with minimal false activations.
High-quality speech recognition and natural-sounding TTS.
User-friendly interface (mobile/desktop or standalone device).
Thorough documentation, including setup and maintenance guidelines.
Timeline:
Estimated project completion: [Insert your preferred timeline, e.g., 3-6 months].
Milestone-based payment structure.
Budget:
TBC
Interested candidates or teams, please provide:
Portfolio of similar projects you’ve worked on.
Breakdown of your approach to tackling this project.
Estimated project timeline and team composition.
Budget proposal and payment structure.
We are looking for highly skilled professionals who are passionate about AI-driven technology and can deliver a product that matches today’s top voice assistants in terms of performance and quality.