City and County Names Misunderstood on Spanish Phone Line #1398
Description
What’s happening:
When someone calls into the Spanish-language version of the phone system and says a city, town, or county name (e.g., “Middletown, Connecticut” or “Cromwell”), the system frequently misunderstands or mis-transcribes what was said.
Why this happens:
The phone line is configured to recognize Spanish speech, which means it tries to interpret everything — including place names — as if it’s being spoken in Spanish. So when someone says an English name, the system doesn’t “hear” it the way it was intended, leading to incorrect transcriptions.
This is especially problematic in the U.S., where almost all cities, counties, and states are named in English, even when the caller is otherwise speaking Spanish.
🛠️ Workarounds & Possible Fixes
✅ 1. Override the Expected Language (Force English for Place Names)
We can adjust the system to treat certain parts of the input (like city names) as if they’re being spoken in English, even when the rest of the call is in Spanish.
Pros:
Simple to implement.
Helps in many U.S.-based cases where the name is clearly English.
Cons:
Not perfect — if a name is said with a strong accent or if the speaker uses Spanish pronunciation, it can still be misheard.
Doesn’t help in countries where city and town names are in other languages (e.g., Mexico, Canada, etc.).
Doesn’t scale well outside the U.S.
Twilio allows us to provide a list of expected city or town names (called “hints”), which helps the system guess correctly.
Pros:
Improves accuracy for known, expected place names.
Cons:
The list can get very large and hard to manage.
Doesn’t help with names we didn’t anticipate or misspellings/mispronunciations.
Still limited by the language setting of the phone line.
🧠 More Robust (But More Complex) Solution
💬 3. Record the Caller’s Speech and Use External Transcription
Instead of trying to recognize the city name in real time, we can record what the person says and then send that recording to a more advanced speech-to-text service (like Google, Deepgram, or Azure), which can:
Automatically detect the language being spoken
Handle mixed-language inputs (e.g., Spanish conversation + English place names)
Provide more accurate transcription, even for unusual or accented names
Once we have the transcription, we can match it to a location and respond accordingly (e.g., send meeting info via text or connect the caller to the right person).
Pros:
Highly accurate across languages and accents
Scales globally — works for U.S. and international place names
Opens the door for richer NLP features (e.g., extracting keywords, detecting intent, etc.)
Cons:
More technical setup required
Slight delay between caller speaking and system response
Requires integration with external services (and likely extra cost)
📌 Summary
This issue arises because the phone system listens for only one language at a time, which leads to misunderstandings when people speak place names in English during a Spanish-language call. There are a few partial fixes — like overriding the recognition language or adding hints — but they only go so far and mainly help in U.S.-specific use cases.
For broader, long-term accuracy — especially in multilingual contexts — recording and transcribing the speech externally is the most flexible and scalable approach.