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Automated speech to text

The most advanced speech recognition software for media content

Perfect Memory’s automated speech to text tool is the most advanced speech recognition software for media content. Based on artificial-intelligence and deep neural networks, it automatically converts speeches into highly accurate captions.

What is AI-based automated speech to text?

An automated speech to text feature allows to automatically transcribe audio and video content into text. It offers great accuracy to quickly generate captions, metadata, annotation and more. This allows to obtain precisely annotated content, easy to find and share with your coworkers, clients and partners.

Quick definition

Speech-to-text, or voice-to-text, is a process that consists in transcribing a speech pronounced by a speaker into textual content in an automated way.

This speech can whether be extracted from audio or video files, such as an audio recording, an interview, a sequence from a TV program, etc.

How does it work?

Automated speech to text transcription involves both linguistics and computational sciences.

The process begins with information extraction, as the sound is extracted from a video or an audio file. Then this information is analyzed in order to comprehend the topic that is currently discussed.

Our automatic voice recognition software allows to detect human language and process it using deep learning algorithms. The audio is then transcribed into text within no turnaround time, as artificial intelligence takes care of it.

How to use AI-based automated speech to text?

Perfect Memory’s speech-to-text feature is very simple to implement. This state-of-the-art voice transcription software will allow to automate all of your content annotation and indexation, for significantly improved ROI.

What are the key features?

The main features of Perfect Memory’s software include:

  • Speech and language processing : our speech-recognition tool is able to recognize human voice with incredibly high accuracy
  • Transcription from audio to text : speech-to-text uses machine learning to convert audio into accurate transcripts
  • Metadata generation: for accurately described, easily searchable content
  • Speaker recognition : able to tell who is speaking among multiple speakers
  • Fully automated : no need to hire transcribers, the artificial intelligence handle everything

Using sophisticate machine-learning algorithms, Perfect Memory’s speech-to-text application automatically detects background noise and handles various languages and accents.

Who needs automated speech to text?

Every organization that manages media contents containing sound, and want to effectively index and label this content, may need speech-to-text. This feature is particularly suitable for media companies who need their content quickly and accurately described.

Speech-to-text AI can be useful for captioning, as it generates automatic subtitles, improving content accessibility. It also facilitates part of speech tagging, as well as retrieval of a certain sequence by searching specific keywords.

Automated speech-to-text makes it easier for journalists to search a specific transcribed verbatim within the content.

Speech-to-text transcription with incredible accuracy

Perfect Memory’s solution offers many automated features to generate the most accurate descriptions, making content indexing way easier.

Combined with video analysis, the software can recognize specific faces and goes beyond speaker recognition, to reveal when each participant appears in the video content. Using semantic segmentation annotation, it detects any instance appearance and describes it precisely, providing users with annotated, easily searchable content.

Our speech to text AI tool

Your audio or video content is processed via different layers, enabling our automated speech to text feature to figure out who speaks, about what subject, with whom, or when the speaker appears in the picture through named entity recognition.

Our automated speech-to-text tool is able to handle multilingual audio content thanks to natural language processing, allowing to access and manage various contents from all over the world. It then processes text data through sentiment analysis to fully understand its meaning and nuances.

Use cases & examples of speech to text applications

Here are some use-cases of Perfect Memory’s automated speech-to-text solution:

Radio France

This media company produces thousands of contents, such as interviews, podcasts, etc. Therefore, they needed to automate their transcription processes through an efficient speech transcription service, in order to index all of this content.

Perfect Memory deployed the right solution to extract, analyze and transcribe all of this audio and video content into text, saving them a lot of time and optimizing content indexing.

Eurovision

Eurovision sets up the technical infrastructure for all of the major international events such as G20, Eurovision song contest, summits and conferences, etc. All of this content had to be accurately described and labelled, in order to be easily exploited and shared.

Perfect Memory’s solution allowed to create a platform specially dedicated to journalists, NGOs, and more, so they could easily access the content they needed. The software helped process all the content sections where people have discussed, to industrialize content description and save the company a precious amount of time.

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