Choosing the Right Open Source Speech to Text Software

Open source speech to text technology processes audio signals using speech recognition techniques to convert spoken content into editable text form. Its applications include real-time captioning, voice search, audio content analysis, etc.

It offers advantages such as improving information retrieval efficiency, supporting multiple languages and dialects, and promoting innovation.

• Part 1: Pros and Cons of Open Source Speech to Text
  • Pros of Speech to Text Open Source
  • Cons of Speech to Text Open Source:
• Part 2: Alternatives to Open Source Speech to Text Software
• Part 3: Top 5 Open Source Speech to Text Software
  • 1. Kaldi
  • 2. Whisper
  • 3. DeepSpeech
  • 4. PaddleSpeech
  • 5. Flashlight ASR

Part 1: Pros and Cons of Open Source Speech to Text

Before we begin introducing open source speech to text software, we'd like you to understand their advantages and disadvantages.

Based on the advantages and disadvantages mentioned above, we recommend using professional speech-to-text software that is not open-source. However, if you still prefer to use open source speech to text software, you can proceed to part 3 for more information.

Part 2: Alternatives to Open Source Speech to Text Software

So, based on the advantages and disadvantages of open-source speech-to-text software introduced in the previous section, iMyFone VoxBox is the professional speech-to-text software we want to introduce to you. You can upload audio files or record directly to convert them into text. Additionally, VoxBox supports four common devices (Windows, Mac, iOS, Android).

Step-by-Step Guide to Convert Speech to Text

Converting speech to text with VoxBox is exceptionally simple. It only requires three easy steps to get it done.

Step 1: Click the button below to download and install VoxBox, then launch the software.

Step 2: Once VoxBox is opened, click on the "Speech to Text" button in the left-hand menu. Now, you can click the "+ Add File" button to import your file.

Step 3: After importing the file, you can choose the language of your file's content for accurate recognition. You can also choose whether to include punctuation. Once all settings are complete, click "Convert" to start converting your speech to text.

Part 3: Top 5 Open Source Speech to Text Software

1. Kaldi

Kaldi is an open-source speech recognition toolkit written in C++, designed for speech recognition and signal processing, provided freely under the Apache License v2.0. A major advantage of this open-source software is its cross-platform compatibility, allowing usage on devices running Windows, Linux, and MacOS.

2. Whisper

Whisper is an automatic speech recognition (ASR) system trained on a vast dataset of multilingual and multitask supervised data collected from the internet, totaling 680,000 hours. It is capable of transcribing multiple languages and translating them into English.

The architecture of Whisper is a simple end-to-end approach implemented in the form of an encoder-decoder Transformer. The input audio is segmented into 30-second chunks, converted into log mel-spectrograms, and then passed to the encoder.

3. DeepSpeech

DeepSpeech is an open-source Speech-To-Text engine that utilizes machine learning techniques trained on research papers from Baidu Deep Speech. The DeepSpeech project leverages Google's TensorFlow to simplify implementation.

It offers specialized wrappers for Python, C, .Net Framework, and Javascript, allowing users to utilize the tool regardless of the programming language they prefer.

4. PaddleSpeech

PaddleSpeech is an open-source integrated speech toolkit designed to facilitate the development and research of speech processing technology by providing an easy-to-use command-line interface and a simple code structure.

It achieves competitive or state-of-the-art performance on various speech datasets and implements popular methods. PaddleSpeech also offers recipes and pre-trained models for quickly reproducing the experimental results mentioned in this article.

5. Flashlight ASR

The ASR application of Flashlight (formerly known as the wav2letter project) provides training and inference capabilities for end-to-end speech recognition systems. In addition to the original research conducted with Flashlight and wav2letter, the codebase also includes the latest architectures and implementations developed in the field of speech.

Conclusion

Nowadays, there are relatively few open-source speech-to-text software options available on the market, with many being outdated versions. Therefore, we have gathered these five speech-to-text software options to the best of our ability for you to choose from.

Additionally, we have introduced VoxBox, a non-open-source speech-to-text software, which may surprise you with its effectiveness. If you are interested in trying it out, the button below can assist you.