Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
We provide solutions to make audio content accessible to everyone. Our offerings enable you to generate text and subtitles from both audio and video files, with options for automatic transcription refined by your input or crafted by our skilled language professionals and experienced subtitlers. To get started, simply upload your media file. Once uploaded, our advanced speech recognition technology or dedicated transcribers will take care of your needs. Your audio will be seamlessly linked to text within our user-friendly online editing platform, allowing you to easily revise, highlight, and search your document. This service is perfect for transcribing research interviews and lectures, ensuring compliance with digital accessibility standards, and incorporating transcriptions and subtitles into the workflows of universities and institutions. Enhance your interviews by making your content editable, searchable, and more accessible. Additionally, you can record interviews or meetings directly using our app and quickly upload the audio to Amberscript for immediate transcription. With our services, transforming your audio into accessible text has never been simpler.
Description
IBM Watson® Speech to Text technology offers rapid and precise speech transcription across various languages, catering to diverse applications like customer self-service, support for agents, and speech analytics. You can quickly initiate your experience using our sophisticated machine learning models right away or tailor them specifically to your needs. Leverage a Watson-driven virtual assistant to handle frequent inquiries in call centers over the phone. Enhance call center efficiency by analyzing conversation records to swiftly spot emerging trends, customer issues, sentiments, non-compliant actions, and more. AI-driven real-time support can significantly elevate agent productivity and success during customer interactions by facilitating instant access to relevant documents and intranet data. As agents engage with customers, Watson actively monitors the dialogue, transcribes the conversation, retrieves pertinent information from resources, and delivers responses to the agent almost instantaneously, thereby streamlining the service process. This innovative approach not only improves the overall customer experience but also empowers agents to provide more informed responses.
API Access
Has API
API Access
Has API
Integrations
IBM Cloud
IBM Cloud Pak for Applications
IBM Watson
Kaltura
Mediasite
Unremot
Integrations
IBM Cloud
IBM Cloud Pak for Applications
IBM Watson
Kaltura
Mediasite
Unremot
Pricing Details
$10 per hour of audio or video
Free Trial
Free Version
Pricing Details
$0.01 per minute
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Amberscript
Founded
2017
Country
Netherlands
Website
www.amberscript.com/en/
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/cloud/watson-speech-to-text
Product Features
Transcription
AI / Machine Learning
Annotations
Audio/Video File Upload
Automatic Transcription
Collaboration Tools
File Sharing
For Manual Transcription
Full Text Search
Multi-Language Support
Natural Language Processing (NLP)
Playback Controls
Speech Recognition
Subtitles
Text Editor
Timecoding
Product Features
Transcription
AI / Machine Learning
Annotations
Audio/Video File Upload
Automatic Transcription
Collaboration Tools
File Sharing
For Manual Transcription
Full Text Search
Multi-Language Support
Natural Language Processing (NLP)
Playback Controls
Speech Recognition
Subtitles
Text Editor
Timecoding