Building a Simple Speech Synthesis System with iFlytek WebAPI in Python

Background: The author is interested in voice synthesis and wants to convert e‑books into audio using a small, self‑built system.

Voice Synthesis System: By leveraging public APIs from various vendors, the development difficulty is reduced to a few API calls, allowing the creation of a compact speech synthesis application.

Preparation: Install Anaconda, Python 3.7, and Visual Studio Code on the development machine.

Steps: Use iFlytek Open Platform's WebAPI. Create an application in the iFlytek console, then navigate to the online streaming TTS section to obtain the three required credentials: APPID, APISecret, and APIKey.

Code Implementation: Install the required Python packages with pip install websocket-client and pip install playsound . Define a play class containing initialization, audio playback, voice selection, and TTS request methods.

Credential Insertion: Fill in the obtained APPID, APIKey, and APISecret in the class constructor.

Modified Demo: The original iFlytek Python demo is adapted to simplify usage. It includes imports, constant definitions, a Ws_Param class for parameter handling, and functions for WebSocket callbacks ( on_message , on_error , on_close , on_open ).

WebSocket Workflow: The on_open function sends JSON‑encoded TTS parameters, receives base64‑encoded audio frames, writes them to a temporary PCM file, and closes the connection when the final frame is received.

Audio Conversion: The pcm2wav function reads the PCM data and writes it to a WAV file with appropriate audio parameters (1 channel, 16‑bit, 16 kHz).

Final Result: After running the script, a complete speech synthesis system is realized, demonstrating how cloud services lower the barrier for AI development without requiring deep knowledge of synthesis algorithms.