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AI-powered, automated, and super-accurate speech recognition infrastructure tool for all of your audio and video data.
Made with ❤️ and ☕ in Bucharest
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Our automatic speech recognition technology ensures a high-level of accuracy for all speakers, converting written numbers into digits.It recognizes entities, such as individual and company names, dates, and locations within your audio files.
Speaker 1
Thank you so much, Mr. Fairbase. Can you please provide your national insurance number?
Speaker 2
National insurance number is 369-4456.
Speaker 1
Wonderful. Also, Mr. Fairbase, can I please have your date of birth?
Speaker 2
My date of birth is 9-26-1995.
Speaker 1
Thank you, George Washington. What is your date of birth?
Speaker 2
It is July 1st, 1968.
Speaker 1
Thank you very much. And can you confirm the address that we have for you here in the system?
Speaker 2
The address is 2898 Atwood Terrace, Columbus, Ohio, 432-24
Speaker 1
All right. We can have your Wi-Fi installed by April 25th.
Speaker 2
Let me see. April the 25th. I believe that's a Monday. You know what? I am working that day, Monday. Do you have... I am off on the 27th. If you can have a technician come out.
Speaker 1
Let's see. 27th. Yeah, I can definitely schedule an appointment for that day. Did you have a preferred time on the 27th you wanted us to come in.
Speaker 2
Yeah. How about in the morning, 9 o 'clock?
Speaker 1
9 o' clock, perfect. So your appointment is set and there is a two-hour window.
Our automatic speech recognition (ASR) technology understands and transcribes speech fast and with over 90% accuracy rate.
Studying how much people talk and when they're quiet helps us understand their feelings and how happy they are. We also look for specific words to see what the agent did and decide what needs urgent focus.
Find key words and related terms to figure out the risk level in certain types of calls.
The software checks how closely a contact center agent follows the script, comparing what they say to the planned words.
1import requests
2
3url = "https://vatis.tech/api/v1/files/transcribe/file"
4
5payload = {
6 'language': 'ro_RO'
7}
8
9files = [
10 ('file', open('/path/to/your_file.mp4','rb'))
11]
12headers = {
13 'Authorization': 'Bearer *your_api_key_here*',
14}
15
16response = requests.request("POST", url, headers = headers, data = payload, files = files)
17
18print(response.text.encode('utf8'))Are you dealing with a large volume of video data? Integrate Vatis Tech's Speech-to-Text APIs easily into your application using just one API call and easy documentation.
We've prepared a short video tutorial to showcase the seamless functionality of our speech analytics software:
Keep track of rules to lower legal issues by spotting and fixing actions that don't follow the rules.
Understand what customers want and feel by analyzing how they talk.
Check if agents stick to their scripts by reviewing call texts to find deviations and guide training.
Make things run smoother by spotting slow processes and making fixes, like creating self-help options for common questions.
Learn from the best sales calls to improve sales strategies.
Watch customer calls as they happen to quickly solve problems or give extra help.
Can’t find the answer you're looking for? Reach out to our Support team.
Speech analytics is the process of analyzing voice recordings to extract insights. It identifies patterns, emotions, keywords, and sentiments in customer service calls, helping businesses improve service, monitor compliance, and understand customer needs. By analyzing how and what customers are saying, businesses can make informed decisions to improve their products, services, and customer interactions.
Speech analytics is used to gain customer insights, improve service quality, ensure compliance, enhance employee training, identify trends, resolve issues quickly, and support data-driven business decisions.
No, NLP (Natural Language Processing) and speech analytics are not the same, although they are related fields. NLP (Natural Language Processing) is an AI field focused on enabling computers to understand human language, while speech analytics is an application of NLP that analyzes spoken language, particularly in business settings, for insights and trends.
No, NLP (Natural Language Processing) and speech recognition are not the same. NLP deals with understanding and interpreting human language by computers, while speech recognition focuses specifically on converting spoken words into text.
Yes, using speech analytics in a call center is more beneficial compared to traditional methods due to several reasons:
Traditional call center methods, prior to speech analytics, included random call sampling, live call monitoring by supervisors, evaluations using standardized checklists, post-call customer surveys, agent self-assessments, and analysis based on basic call metrics like duration and volume. These methods were very time-consuming and less comprehensive compared to modern speech analytics.
Your data stays protected with our strict zero-retention policy. We ensure GDPR compliance and offer flexible deployment in the EU, USA, or other global locations - giving you control over your data security.
AI-powered, automated, and super-accurate speech recognition infrastructure tool for all of your audio and video data.
Made with ❤️ and ☕ in Bucharest
