Imagine a blind taste test, like the famous Pepsi vs. Coke challenge, only here, 269 crowd-sourced listeners in the United States compared the same voice recordings enhanced by Tomato.ai, Sanas, and Krisp. Across 17 Filipino and Indian accent and noise scenarios, they cast 18,536 votes, delivering statistically significant insights. The result? Tomato.ai emerged as the favorite among listeners who judged it against Sanas and Krisp using the same samples referenced in Krisp’s own blog.
Overall Preference
(% of >750 votes per row)
| Option A | % | Option B | % | Tie % | Winner |
|---|---|---|---|---|---|
| Tomato.ai | 65.0% | Sanas | 16.6% | 18.4% | Tomato.ai |
| Tomato.ai | 40.6% | Krisp | 31.7% | 27.8% | Tomato.ai |
| Krisp | 66.8% | Sanas | 9.6% | 23.6% | Krisp |
How the Study Was Conducted
Side-by-side comparisons were crowdsourced using the Amazon Mechanical Turk platform using individuals based on the United States. Individuals shared their preferences across the following key metrics which matter most in live customer calls.
- Preference reflects the overall listener choice, showing which audio they’d rather hear, critical for keeping customers engaged.
- Intelligibility measures how easily words are understood, directly reducing repeats and lowering Average Handle Time (AHT).
- Acoustic Quality captures the clarity and richness of the sound, which shapes trust and professionalism in the customer’s mind.
- Accent Softening measures the reduction of heavy accent traces, helping customers process speech faster and reducing bias that can hurt satisfaction scores.
- Naturalness assesses how human and unprocessed the voice sounds, which impacts comfort.
Together, these metrics provide a complete picture of how well a solution supports faster resolutions, higher First Call Resolution (FCR), and improved Customer Satisfaction (CSAT).
Tomato.ai vs Sanas
(% of >750 votes pre row)
| Metric | Tomato.ai % | Sanas % | Tie % | Winner |
|---|---|---|---|---|
| Preference | 65.0% | 16.6% | 18.4% | Tomato.ai |
| Intelligibility | 57.7% | 11.4% | 30.9% | Tomato.ai |
| Acoustic Quality | 63.7% | 14.3% | 22.0% | Tomato.ai |
| Accent Softening | 52.2% | 16.1% | 31.7% | Tomato.ai |
| Naturalness | 32.9% | 41.6% | 25.5% | Sanas |
Tomato.ai vs Krisp
(% of >750 votes per row)
| Metric | Tomato.ai % | Krisp % | Tie % | Winner |
|---|---|---|---|---|
| Preference | 40.6% | 31.7% | 27.8% | Tomato.ai |
| Intelligibility | 33.7% | 21.3% | 45.0% | Tomato.ai |
| Acoustic Quality | 45.6% | 17.9% | 36.6% | Tomato.ai |
| Accent Softening | 36.6% | 15.3% | 48.1% | Tomato.ai |
| Naturalness | 21.0% | 43.7% | 35.3% | Krisp |
Krisp vs Sanas
(% of >750 votes pre row)
| Metric | Krisp % | Sanas % | Tie % | Winner |
|---|---|---|---|---|
| Preference | 66.8% | 9.6% | 23.6% | Krisp |
| Intelligibility | 55.8% | 6.4% | 37.8% | Krisp |
| Acoustic Quality | 66.4% | 6.9% | 26.7% | Krisp |
| Accent Softening | 39.7% | 10.9% | 49.4% | Krisp |
| Naturalness | 36.2% | 25.8% | 38.1% | Krisp |
Audio Latency
| Vendor | Latency on Lower End PC (4th gen intel core i5, 8 GB memory) |
Latency on Higher End PC (12th gen intel core i5, 16 GB memory) |
|---|---|---|
| Tomato.ai | ~220 ms (medium accent) ~500 ms (heavy accent) |
~220 ms (medium accent) ~500 ms (heavy accent) |
| Krisp | ~400 – 1,000 ms | ~220 ms |
| Sanas | Error message for CPUs older than 8th gen intel core i5 |
~350 – 450 ms |
Tomato.ai’s latency is less affected by how powerful the agent’s PC is because the Accent Softening AI model is hosted on the cloud (nearby the agent’s location) offloading resource usage to a cloud-hosted GPU. Both Sanas and Krisp have the AI model on the PC, so lower-end PCs can run out of resources, which significantly increases latency. Krisp, at times, can handle lower end PCs by automatically downgrading to a smaller AI model that consumes fewer resources, but at the expense of quality.
What This Means for Your Business
-
- Intelligibility & Accent Reduction: Tomato.ai’s strong showing here ensures customer comprehension and streamlined call resolution, directly boosting CSAT and FCR scores.
- Acoustic Quality: Rich, clean audio reinforces trust and perceived professionalism, elevating customer experience.
- Naturalness: Though slightly behind, Tomato.ai’s naturalness remains high, balancing fluid speech with accent softening, without sacrificing clarity.
Why Tomato.ai Moves your Call Center KPIs
Designed for outcomes, not demos. Tomato.ai focuses on the three drivers that most reliably lift AHT, FCR, and CSAT: intelligibility, accentedness reduction, and acoustic cleanliness.
- Faster resolutions → Lower AHT & higher FCR
- Higher intelligibility means fewer back‑and‑forths, fewer repeats, and faster comprehension of names, numbers, and addresses.
- FConsistent clarity in noise keeps agents productive during peak conditions and reduces repeat calls.
- Happier customers → Higher CSAT & NPS
- Less perceived effort: Reducing accent traces lowers cognitive load for customers and reduces frustration.
- Confidence & trust: Clean, artifact‑free audio sounds more professional and improves brand perception.
- Better QA & compliance
- Clearer recordings improve transcription accuracy and make PCI/PII redaction more reliable.
- Coachability: QA teams can pinpoint issues quickly when speech is easier to parse.
Main Takeaway
- Tomato.ai is most preferred in blind listening tests (269 listeners provided thousands of votes across audio pairs and metrics), a strong endorsement of user satisfaction.
- Tomato.ai’s Latency is well within the usable range for call centers that require real-time performance.
In sum, Tomato.ai not only matches or surpasses Sanas and Krisp on the metrics that matter most but also wins listener preference, making it the most compelling choice for businesses that prioritize effective, real-time accent softening without sacrificing audio quality.
Comparing Audio Samples
| # | Observations | Audio |
|---|---|---|
| 1 |
|
Original Sanas Krisp Tomato.ai |
| 2 |
|
Original Sanas Krisp Tomato.ai |
| 3 |
|
Original Sanas Krisp Tomato.ai |
| 4 |
|
Original Sanas Krisp Tomato.ai |
| 5 |
|
Original Sanas Krisp Tomato.ai |
| 6 |
|
Original Sanas Krisp Tomato.ai |
| 7 |
|
Original Sanas Krisp Tomato.ai |
| 8 |
|
Original Sanas Krisp Tomato.ai |
| 9 |
|
Original Sanas Krisp Tomato.ai |
Capabilities Compared
| Tomato.ai | Krisp | Sanas | |
|---|---|---|---|
Accent Softening Robustness |
|||
| Supported Accents |
|
|
|
| Modes of operation |
|
|
|
| Scalable range of output voices |
|
|
|
| Accent leakage |
|
|
Consistently observed leakage |
| Background noise and voice cancellation robustness | Highly robust, automatically included in the Accent Conversion models | Highly robust, automatically included in the Accent Conversion models | Very limited |
| Agent and customer-side noise cancellation | Bi-directional, automatically included in the Accent Softening models | Bi-directional, automatically included in the Accent Conversion models | Customer-side only |
| Headset robustness | Highly robust (no specific headset requirement) | Highly robust | Requires specific headsets |
| Robustness across users | Works consistently across all users | Works consistently across all users | Requires testing three different versions for each user |
| Wrong pronunciations | Some | Some | Noticeably more frequent |
| Preserves user’s voice | Yes | Yes | Limited |
| User enrollment needed | Limited (onboarding requires recording 10 seconds) | No | No |
| Dynamic adaptation to new speakers | Yes, within the same or different call, regardless of the gender | Yes, within the same or different call, regardless of the gender |
|
| Voice quality | 16khz (wide-band, VOIP, industry-leading voice quality) | 16khz (wide-band, VOIP, industry-leading voice quality) | 8kHz only |
Noise Cancellation robustness |
|||
| Voice quality and noise cancellation | Keeps voice audible, while removing thousands of noise types | Overly aggressive noise cancellation can make the primary speaker’s voice hard to hear, or even fully silence it | Leaks certain noises, and the voice quality can degrade |
| Agent-side Background Voice Cancellation | Included | Included | Does not remove well secondary and background voices (i.e. other people speaking around the primary speaker) |
| Customer-side Noise Cancellation | Included | Included | Not available |
| Acoustic Echo Cancellation | Included | Included | Not available |
| Voice quality |
|
|
8kHz only |
Application and audio drivers robustness |
|||
| CPU utilization |
|
|
|
| Audio drivers | Highly reliable and tested | Highly reliable and tested for 7+ years | Users often need to restart the drivers to avoid breakdown of mic and speaker audio streams. |
| Headset and application compatibility | Compatible and tested with most headsets and voice applications used in call centers | Compatible and tested with most headsets and voice applications used in call centers | New entrant, minimal deployments and testing |
Management and deployment at scale |
|||
| Supported platforms | Win | Win, Mac, Linux, Chrome, VDI | Win |
| Installation package | Single installation includes the universal accent solution and noise cancellation | Single installation package including all accent packs and noise cancellation |
|
| SSO authentication |
|
|
|
| Remote deployment and settings for admins | Highly Scalable | Highly Scalable | Very Limited |
| App version management and auto-update | Highly Scalable | Highly Scalable | Very Limited |
| Analytics for Accent Conversion, Noise Cancellation and platform usage | Available | Available | Not available |
| Enterprise-Grade Support |
|
|
|