Day 2: Integrating AI-Powered Speech-to-Text for Call Handling #AIVoiceBot #STTIntegration

AI-powered speech-to-text (STT) enables our Laravel call center AI to convert customer calls into text, analyze queries, and respond accurately. Today, we’ll integrate OpenAI Whisper, AWS Transcribe, or Google Speech-to-Text to process voice input.

Table of Contents

🎙️ 1. Choosing a Speech-to-Text (STT) API

To transcribe customer calls, we need an AI service for real-time voice-to-text conversion:

🔹 OpenAI Whisper – Highly accurate and supports multiple languages.
🔹 AWS Transcribe – Works well with call centers and supports speaker identification.
🔹 Google Speech-to-Text – Offers real-time transcription with punctuation.

🔗 More about AI STT APIs:

🛠️ 2. Setting Up Laravel for Speech-to-Text

📌 Step 1: Install Dependencies

For OpenAI Whisper:

composer require openai-php/client

For AWS Transcribe:

composer require aws/aws-sdk-php

For Google Speech-to-Text:

composer require google/cloud-speech

🎤 3. Implementing Speech-to-Text in Laravel

📌 Option 1: OpenAI Whisper STT

namespace App\Services;

use OpenAI;

class SpeechToTextService
{
    protected $client;

    public function __construct()
    {
        $this->client = OpenAI::factory()->withApiKey(env('OPENAI_API_KEY'))->make();
    }

    public function transcribeAudio($audioFilePath)
    {
        $response = $this->client->audio()->transcriptions()->create([
            'model' => 'whisper-1',
            'file' => fopen($audioFilePath, 'r'),
            'language' => 'en',
        ]);

        return $response['text'] ?? 'Unable to transcribe.';
    }
}

Example Usage in Controller

use App\Services\SpeechToTextService;

public function handleVoiceRequest(Request $request)
{
    $stt = new SpeechToTextService();
    $text = $stt->transcribeAudio($request->file('audio'));

    return response()->json(['transcription' => $text]);
}

📌 Option 2: AWS Transcribe STT

use Aws\TranscribeService\TranscribeServiceClient;

class AWSSpeechToText
{
    protected $transcribe;

    public function __construct()
    {
        $this->transcribe = new TranscribeServiceClient([
            'region' => 'us-east-1',
            'version' => 'latest',
            'credentials' => [
                'key' => env('AWS_ACCESS_KEY_ID'),
                'secret' => env('AWS_SECRET_ACCESS_KEY'),
            ],
        ]);
    }

    public function transcribe($audioFileUrl)
    {
        $result = $this->transcribe->startTranscriptionJob([
            'TranscriptionJobName' => 'CallCenterTranscription',
            'LanguageCode' => 'en-US',
            'Media' => ['MediaFileUri' => $audioFileUrl],
            'MediaFormat' => 'mp3',
        ]);

        return $result['TranscriptionJob']['TranscriptionJobStatus'];
    }
}

🔹 Note: AWS processes audio asynchronously, so we need to check the job status periodically.

📞 4. Using STT for Call Center Conversations

Once we transcribe customer speech, we process it with our AI bot.

📌 Example: Pass Transcribed Text to AI for Response

use App\Services\AIService;
use App\Services\SpeechToTextService;

public function processVoiceQuery(Request $request)
{
    $stt = new SpeechToTextService();
    $query = $stt->transcribeAudio($request->file('audio'));

    $ai = new AIService();
    $response = $ai->generateResponse($query);

    return response()->json(['reply' => $response]);
}

🎤 5. Testing the AI Call Center STT System

1️⃣ Record a voice query (e.g., “What’s my account balance?”).
2️⃣ Upload the audio file via API request.
3️⃣ STT converts it to text.
4️⃣ AI bot processes the text and generates a response.
5️⃣ The response is converted back to speech (coming in Day 3).

📝 Meta Description

“Integrate AI-powered speech-to-text (STT) in a Laravel call center bot using OpenAI Whisper, AWS Transcribe, or Google Speech-to-Text. Automate call handling with AI! #AIVoiceBot #STTIntegration”

💡 Next: Day 3 – Converting AI Responses into Realistic Speech with Text-to-Speech (TTS) #AIVoiceBot #TTSSynthesis

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