Deep Voice Recognition

Empower your business with the power of Voice

The ProAutomate "Voice Recognition" Artificial Intelligent System is highly customizable with other third-party algorithms to get best-of-the-breed and cutting-edge Voice technology to suit specific and localized requirements.

ProAutomate's deep voice recognition is the first step in enabling voice-activated applications to process speech. Like other natural language processing applications, ProAutomate uses a wealth of diverse training data. Speech samples collected from a broad range of participants and several environments are used in ProAuotmate's voice recognition to correctly recognize, process, and respond to voice commands.

ProAutomate is designed to understand human spoken language expressed in a natural way by converting speech-to-text in real-time, using "Deep Neural Network" learning models.

ProAutomate has a robust speech recognition platform, and its AI & RPA solutions have become better by managing challenges such as regional accents and background noise. With the implementation of NLP (natural language processing) and NNT (neural network technology) ProAutomate has improved the speech and voice technology to stay on par with humans. Backed by machine learning capabilities, ProAutomate can train it to pick keywords and phrases and perform sentiment analysis, keyword density, and identifying multiple languages and pull meaning full insights to retrain the model.


Voice Recognition Solution


Voice Commands

  • Invoking "Voice Command" UI (VCUI) presents the user with ProAutomate UI to start accepting voice commands. The VCUI is highly customizable based on preferences and needs. Each of the voice commands executes a pre-defined service action that will be processed by the ProAutomate application.

Dictation Commands

  • ProAutomate is capable of enabling a program or system to process human speech by converting spoken words into computer text using automatic speech recognition for authenticating users via their voice and action-based instructions defined by the human. Dictations are typically processed near real-time OR batch processes for providing clinical notes, transcripts, etc.

Voice Retrieval

  • ProAutomate uses regular phone systems to listen to certain parts of patient EMR using a separate Text-to-Speech AI algorithm.

Voice Transcription


Powerful Transcription Engine

  • ProAutomate leverages NLP to accurately convert and transcribe saved audio and video files to readable and meaningful text.

Speaker Identification

  • ProAutomate uses sophisticated acoustic algorithms to recognize multiple speakers’ voices from multiple channels or sources in the same audio source.


  • Designed to provide automated transcripts with accuracy for a wide range of audio and video file types.

Voice Analytics using NLP


Keyword Extraction

  • With ML algorithms, ProAutomate enables the extraction of the most frequently used keywords or information to plan the direction and strategy for upcoming calls or analyze call history.

Confidence Score

  • The confidence score can help to identify how accurately the system can understand, identify, and categorize the words during transcription.

Entity Identification and Analysis

  • Help establish relationships between the topics and content while the conversation is in place.



Clinical Notes

  • Healthcare professionals will be capable of capturing their notes and receive clinical decision support during the appointment with digital voice recognition assistants that are able to update EHRs with relevant information and submit prescriptions for doctor’s review and signature by using their voice, and issue commands for navigation inside the system.

Patient-Practioner Communication

  • ProAutomate's AI-powered voice recognition platform can save clinical staff time and assume tasks like appointment scheduling in outpatient settings by offering a voice-powered virtual assistant connecting patients with their caregivers.

Patient Engagement

  • ProAutomate helps in conversationally checking-in with 'at-risk patients' leveraging AI technology. Thousands of dynamic, command-based responses programmed within an EHR system can be substantially reduced for efficient patient engagement and saving time.

By adopting ProAutomate's Voice Recognition platform, a physician practice can realize a 60% decrease in overhead and a 25% increase in patient-engagement throughout and billable revenue.