Handling Code-Switching: Integrating STT for Vietnamese-English Calls

In this article

1. The Challenge of Code-Switching in Speech Recognition
2. Why Monolingual STT Systems Drop Words
3. Impact on Business Operations
4. Technical Solution: Efficient Code-Switching Handling
5. Multilingual-Supportive STT Model
6. Real-Time Integration via WebSocket
7. Integrating Vietnamese-English STT for Calls
8. 1. Infrastructure and API Key Setup
9. 2. Audio Pipeline Setup
10. 3. Response Handling and Business Logic
11. 4. Testing and Optimization
12. Why Choose the AIVISION Solution?
13. Summary

In modern business environments, calls between Vietnamese employees and international clients—particularly native English speakers—frequently involve mixed language use. "Code-switching," the practice of alternating between Vietnamese and English within a single sentence or conversation, is a significant barrier for traditional Speech-to-Text (STT) systems. It often leads to dropped words or missed critical information. This article analyzes the technical challenges of code-switching and demonstrates how to integrate a multilingual STT solution to ensure seamless, uninterrupted call processing.

The Challenge of Code-Switching in Speech Recognition

When a speaker switches from Vietnamese to English, acoustic features change abruptly. STT models trained exclusively on a single language often struggle to adapt to the vocabulary and grammatical structures of the other.

Why Monolingual STT Systems Drop Words

Many legacy systems rely on fixed Language Models (LMs) specific to one language. When a user says, "Cho tôi check đơn hàng order ID 123", a Vietnamese-only model attempts to force English words into a Vietnamese context. This results in spelling errors or the complete omission of key terms.

More critically, in real-time streaming scenarios, sudden changes in audio flow can cause buffer overflows or resets. This leads to "cut-off" errors, where the end of a sentence is lost entirely.

Impact on Business Operations

For enterprises deploying AI for customer care or meeting recording, code-switching errors are not just technical glitches; they are operational risks:

• Data Loss: English technical terms, such as product names or order codes, are often transcribed incorrectly.
• Conversation Disruption: Text-to-Speech (TTS) systems may respond incorrectly due to misinterpreted context, frustrating customers.
• Increased Labor Costs: Teams must perform manual Quality Assurance (QA) to correct transcriptions, slowing down workflows.

Technical Solution: Efficient Code-Switching Handling

To address these issues, AIVISION has developed STT models specifically designed for the Vietnamese market, where language mixing is a common characteristic.

Multilingual-Supportive STT Model

AIVISION Speech-to-Text does not just recognize pure Vietnamese; it effectively handles conversations interspersed with English. The model is trained on a large-scale Vietnamese speech corpus that includes audio samples containing common English vocabulary used in office and business settings.

The key differentiator lies in how the model processes the audio stream:

1. Language Boundary Detection: The system detects shifts in acoustic features to smoothly switch processing contexts.
2. English Word Preservation: English words within Vietnamese sentences retain their correct spelling and context, avoiding incorrect phonetic transliteration into Vietnamese.
3. Word Timestamps: The system provides precise timestamps for each word, allowing developers to identify exactly when language switches occur, which is useful for user behavior analysis.

Real-Time Integration via WebSocket

To prevent cut-off errors in live calls, using the WebSocket protocol is essential. AIVISION provides a streaming API via WebSocket, allowing audio data to be sent in small chunks and text results to be received with low latency.

Technical Integration Notes:

• Chunk Size: Send audio data in reasonable sizes (e.g., 100–200ms per chunk) to balance latency and accuracy.
• Partial Results: Process intermediate (partial) results to continuously update the user interface, creating a sense that the system is actively "listening" and responsive.
• Final Results: Only store and trigger business logic when the final result for a complete sentence or semantic segment is received.

Integrating Vietnamese-English STT for Calls

Here are the practical steps to deploy a code-switching-capable STT system on the s2speech.com platform:

1. Infrastructure and API Key Setup

Create an account on Start free to obtain your API Key. AIVISION services are completely free for all accounts, with daily usage limits that reset at midnight.

2. Audio Pipeline Setup

• Input: Capture audio from telephony lines or microphones.
• Pre-processing: For call centers, ensure audio is converted to the appropriate format (e.g., 8 kHz G.711 μ-law/A-law or 16-bit PCM).
• Transmission: Use a WebSocket client to send binary audio data to the AIVISION STT endpoint.

3. Response Handling and Business Logic

• Receive JSON containing the transcribed text and start/end times for each word.
• Check the final status to confirm the end of a sentence.
• Apply business rules (e.g., extracting order IDs, identifying intent) based on the accurately recognized text.

4. Testing and Optimization

Use real call data to verify accuracy. AIVISION reports an average Word Error Rate (WER) of 10.53% across four Vietnamese test sets. Notably, the ViMedCSS set, which contains many English medical terms, achieves a WER of 14.10%. This demonstrates reliable performance for conversations with mixed languages in enterprise environments.

Why Choose the AIVISION Solution?

AIVISION focuses on building Speech AI solutions specifically for Vietnamese, with experience deploying for hundreds of enterprises in Vietnam, the USA, Mexico, the Philippines, and Thailand.

Key Benefits:

• High Accuracy: WER of 8.3% on the VLSP test set (1,000 utterances with human references).
• Multilingual Support: In addition to Vietnamese and English, the system supports 24 other languages for translation applications.
• Natural TTS Integration: When paired with aiv-tts-S.1.0, the system can read English words within Vietnamese sentences naturally, avoiding robotic pronunciation or incorrect stress.
• Developer-Friendly API: Supports both REST (for file transcription) and WebSocket (for real-time streaming), with OpenAI-compatible endpoints.

If you are facing challenges with multilingual calls or need detailed technical consultation on optimizing your audio pipeline, please Contact the AIVISION technical team for support.

Summary

Handling code-switching in Speech-to-Text systems is no longer a complex problem if you choose the right technology. Instead of relying on monolingual STT models, transition to solutions designed for multilingual support, particularly those optimized for the Vietnamese-English language mix.

AIVISION provides a robust STT and TTS platform, enabling businesses to build seamless, accurate, and efficient voice applications. Start today to enhance customer experience and operational efficiency.

Explore more voice applications on the Blog or Start free to experience AIVISION's speech recognition quality.

Frequently asked questions

What is code-switching in the context of Speech-to-Text?

Code-switching is the phenomenon where speakers alternate between two or more languages (e.g., Vietnamese and English) within the same conversation or even a single sentence. This poses a challenge for monolingual STT models to recognize speech accurately.

Does AIVISION support handling English words within Vietnamese sentences?

Yes. AIVISION Speech-to-Text is trained to effectively handle conversations mixing Vietnamese and English. It preserves the spelling of English words and ensures the sentence context remains accurate.

How can I avoid cut-off errors in real-time STT?

To avoid cut-offs, use the WebSocket protocol with a streaming mechanism. Send audio data in small chunks and process both partial and final results synchronously to maintain a continuous flow.

Does AIVISION charge for using the STT API?

All AIVISION services are completely free for every account. There is no requirement for a credit card or pre-payment. Each account has a daily usage limit, which can be increased upon request.

What is the accuracy of AIVISION Speech-to-Text for Vietnamese-English data?

According to internal measurements, the average WER on Vietnamese datasets is 10.53%. For the ViMedCSS dataset, which contains many English terms, the WER is 14.10%, indicating strong capability in handling conversations with mixed languages.

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