Hinglish, Tanglish, and Tenglish are forms of code-switching where speakers seamlessly blend Indian languages like Hindi, Tamil, or Telugu with English within a single conversation or sentence. This linguistic phenomenon is the natural way hundreds of millions of people in India communicate, moving between languages to express cultural nuances, technical terms, or social identity. We built hearlog to recognize this reality, using Google Gemini to transcribe and translate these mixed-language patterns that traditional monolingual tools often fail to capture.

What is code-switching in the Indian context?

Code-switching is the practice of alternating between two or more languages or varieties of language in conversation. In India, this is not merely a modern trend but a deep-seated linguistic habit. Whether it is Hinglish (Hindi and English), Tanglish (Tamil and English), or Tenglish (Telugu and English), these hybrids allow speakers to bridge the gap between their heritage languages and the global language of business and technology.

Researchers estimate that Hinglish speakers alone number in the hundreds of millions, with some estimates placing the figure at 350 million or more. This makes it one of the most widely spoken "languages" in the world, even though it lacks formal recognition in dictionaries. The mix is rarely random; it follows complex internal grammatical rules that native speakers understand intuitively. For example, a speaker might use English nouns for professional concepts while using Indian verbs and syntax to provide emotional context or sentence structure.

We see this every day in our work at hearlog. Users recording meetings or interviews rarely stick to a single "pure" language. A project manager in Bengaluru might start a sentence in Kannada, switch to English for technical specifications, and end with a Hindi phrase for emphasis. Capturing this "real" speech is the core challenge we address by supporting every major Indian language — Hindi, Tamil, Telugu, Bengali, Marathi and more, plus 50+ world languages.

The rise of Hinglish, Tanglish, and Tenglish

The evolution of these mixed languages is driven by urbanization, the internet, and the unique history of the Indian education system. English often serves as the "link language" in professional settings, but the regional language remains the heart of personal expression. When these two worlds collide, new dialects are born.

• Hinglish: Most prevalent in North and Central India, it has become the default language of Bollywood, advertising, and social media. Phrases like "What is your good name?" or "Adjust kar lo" (Please adjust) demonstrate how English words are adopted into Indian structures.
• Tanglish: Widely spoken in Tamil Nadu and the Tamil diaspora, Tanglish often involves adding Tamil suffixes to English verbs. It is a vibrant part of youth culture in Chennai and is frequently used in Tamil cinema (Kollywood) lyrics.
• Tenglish: Similar to Tanglish, Tenglish blends Telugu with English. It is particularly common in the tech hubs of Hyderabad, where professional terminology is almost exclusively English, but the surrounding conversational framework remains Telugu.

Because these languages are spoken rather than formal, they present a significant hurdle for standard speech-to-text engines. We have designed hearlog to be "language-agnostic" within the Indian context, ensuring that a switch from one language to another does not break the transcription flow.

Why traditional AI struggles with mixed Indian speech

Most transcription services were built for monolingual environments, typically optimized for North American or European English. When these systems encounter a speaker who alternates between languages, they often try to force the sounds into a single language's phonetic map. This leads to what researchers call "word error rate" (WER) spikes.

Studies report that code-switched speech recognition generally results in substantially higher word error rates than monolingual speech. This happens because the AI must not only recognize the word being said but also predict which language the next word will belong to. If a system expects English but hears "bilkul" (certainly), it might transcribe it as a nonsensical English word like "bill cool."

To solve this, researchers at institutions like Microsoft Research India developed the GLUECoS benchmark (ACL 2020), a specialized dataset designed to evaluate how well NLP models handle code-switched Indian languages. This research highlights the complexity of "matrix languages"—the dominant language of a sentence—and "embedded languages"—the words brought in from another tongue.

How hearlog processes real Indian speech

We believe that technology should adapt to how humans speak, not the other way around. Our app is powered by Google Gemini, which utilizes advanced large language models (LLMs) capable of understanding context across multiple languages simultaneously. This allows us to offer features that standard recorders cannot match.

Transcription of mixed-language speech

When you use hearlog for Indian languages, the engine does not just look for a single dictionary. It understands the phonetic and semantic patterns of code-switching. If a user is speaking Tenglish, hearlog identifies the Telugu phonemes and the English technical terms, weaving them into a coherent transcript. You can see this in action by trying our Hindi transcription or Tamil services, where the output reflects the natural mix used in the audio.

Intelligent summaries and translation

Transcription is only the first step. For professionals using hearlog for meeting transcription, the real value lies in the summary. Because our backend understands the underlying meaning of the code-switched text, it can generate a clean, professional summary in English (or any of the 50+ supported languages). This means a meeting conducted in a mix of Marathi and English can be instantly turned into an English action-item list.

Offline-resilient recording

Indian environments often involve inconsistent network connectivity. We built hearlog with offline-resilient recording. This means your audio is saved locally on your device during the recording. If your data connection drops while you are in a basement office or traveling, your audio remains safe. Once you are back online, hearlog automatically uploads and transcribes the file, ensuring no part of the conversation is lost.

The cultural importance of preserving mixed speech

Some linguistic purists argue that Hinglish or Tanglish "corrupts" the original languages. However, linguists increasingly view these as signs of a "living language." Code-switching is a tool for precision. Sometimes, an English word captures a technical nuance perfectly, while a regional word carries an emotional weight that English cannot replicate.

When we compare how hearlog compares to Otter or other global tools, the difference is often in this cultural awareness. A tool that sees "Indian English" as an error will never be useful for a journalist interviewing people in a Delhi market or a researcher conducting focus groups in rural Andhra Pradesh. We prioritize the preservation of the speaker's intent, regardless of which "code" they choose to use at any given moment.

Conclusion

India’s linguistic landscape is one of the most complex in the world. Hinglish, Tanglish, and Tenglish are not just "slang"; they are the primary modes of communication for a significant portion of the global population. At hearlog, we are committed to building tools that respect this complexity. By leveraging the power of Google Gemini and focusing specifically on the needs of Indian speech, we provide a transcription experience that is as fluid and versatile as the people who use it.

Frequently Asked Questions

Is Hinglish considered a real language?

While not a formal "scheduled language" in the Indian constitution, Hinglish is a recognized linguistic phenomenon used by hundreds of millions of people. It follows its own internal rules of grammar and syntax, making it a highly effective and structured form of communication.

How does hearlog handle different Indian accents?

Our app is powered by Google Gemini, which has been trained on diverse datasets including various Indian accents and dialects. This allows us to maintain high levels of accuracy across different regional variations of English and local languages.

Can hearlog translate Hinglish into pure English?

Yes. One of our core features is the ability to take code-switched transcripts and provide a translated summary or a full translation into English or any of the 50+ world languages we support, making it ideal for international business contexts.

Does the app work if I lose my internet connection?

We use offline-resilient recording. While the transcription itself requires a connection to our AI engines, your audio is safely captured and stored on your device locally. It will automatically upload and process as soon as your connection is restored.

Which Indian languages does hearlog support?

We support every major Indian language, including Hindi, Tamil, Telugu, Bengali, Marathi, Gujarati, Kannada, and Malayalam, among others. Our system is designed to handle these languages individually or when they are mixed with English.