How to Create a Voice Translation App

Machine translation, the core technology of real-time and voice translation solutions, registered a dramatic rise with the expansion of machine learning. Here are some market insights.

The machine translation market exceeded $650 million in 2020, with expected growth at a CAGR of 25%, reaching $3 billion by 2027. The increasing demand for enterprise translation software and AI-based voice translation apps significantly affect the market rise.

Voice translation is the next level of translation revolution, providing real-time speech translation for conversations instantly interpreting your speech into a target language.

The core features of voice translation are based on three technologies:

1. Automatic speech recognition (ASR) – The app recognizes your voice and words and transforms them into written text.
2. Machine translation (MT) – The transformed text is translated with a machine translation module.
3. Voice synthesis (TTS) – The translated text is spoken in a target language.

The voice translation technology is still in its development stage, where the greatest potential is still to be revealed.

HOW TO CREATE A VOICE TRANSLATION APP: TECHNICAL ASPECTS

Whether you want to create a voice translation app from scratch or integrate voice translation components, the technology of translation service is almost identical. If we try to put it in simple words, the formula of voice translation consists of two components. It is as follows:

MICROSERVICE

Microservice is implemented on the cloud using Cloud AI features to translate the message:

• Speech-to-Text
• Cloud Translation
• Text-to-Speech

Tasks performed by the microservice:

1. Receives encoded audio messages.
2. Transcribes the audio message with the Speech-to-Text API.
3. Translates the transcribed message with the Translation API.
4. Synthesizes the translated message with the Text-to-Speech API.
5. Stores the translated message in Cloud Storage.
6. Sends the translated response back to the client.

CLIENT APP

On the user side, the client component records audio messages and later downloads the translated message from the Cloud Storage bucket.

Tasks performed by the client app:

1. Records the audio message with the Speech-to-Text API.
2. Encodes the audio message.
3. Sends an HTTP request to the microservice with the encoded audio message.
4. Receives the HTTP response to the locale of the translated audio message from the microservice.
5. Sends a request to the Cloud Storage bucket to retrieve the translated audio message.
6. Plays the translated audio message.

The following diagram shows the interaction of the two components; microservice and the client app.

TECHNOLOGIES USED TO CREATE A VOICE TRANSLATION APP

The latest news predicts AI-based voice recognition and translation technologies will be mainstream. The technologies aimed at automating processes have reached the language translation industry, completely changing its profile. Here are the technologies empowering the new voice translation applications.

Machine Learning in Voice Translation

The brain, composed of approximately 100 billion cells called neurons and connections called dendrites, is at the heart of the branch of Artificial Intelligence known as Machine Learning. The three basic parts of the neurons are the input layer, hidden layer, and output layer, responsible for getting information, processing, and generating results.

The rise of Neural Machine Translation (NMT)

Using the power of artificial intelligence and machine learning algorithms, NMT grabs the whole input sentence or speech and generates the output. Just like a human translator, neural machine translation hears the sentence, catches the meaning, and then translates it.

HOW TO CREATE A VOICE TRANSLATION APP STEP BY STEP

Aside from the technical aspect of voice translation app development, the application development goes through several stages critical for building a competitive application meeting user needs.

Market research: it is the initial and maybe the most critical stage when starting with an application. With market research, you reveal the market’s potential, its trends, make predictions about market growth, and what your value proposition will be.

Competitor analysis: in parallel with market research, the stakeholders carry out competitor analysis to list the popular names, reveal their users, user preferences, which features are most lovable, and more.

Concept finalization: your idea may be too vague. If preceded by market research, it may turn out it is outdated or unrealistic. A more optimal way to have a voice translation app concept is to rely on research data.

App name & logo creation: it should be related to voice translation, easy to remember, and eye-catching.

Real-time translation design: wrap your application and features into a presentable and beautiful “package” that will make users love your app. Here simple UI/UX and accessibility are the priority.

Gamification & engaging functionality: add a fun part to your application to make your app stand out.

Marketing plan: support voice translation app development and deployment with a strong marketing plan, grabbing customers before the app launch.

Security matters: think of a robust security system for your app that will use cloud services and messaging technology.

HOW MUCH DOES IT COST TO CREATE A VOICE TRANSLATION APP?

The approximate voice translation app development cost would be $25.000 – $30.000. The price is calculated based on minimum viable product features without post-release support and maintenance. With each additional feature, the price may slightly or dramatically change.

Moreover, depending on the preset features, the number of platforms, and specific demands, the price may again change during the process. It is hard to give a price estimation to the stakeholders in the initial stages of project discussions, so think of a budget that is no less than $30.000.

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