Olivia Hirschey Marrese
This guest blog was written by Olivia Hirschey Marrese who is a linguist based in Boulder, CO. She is currently pursuing her PhD in linguistics at the University of Colorado, where she researches conversations in English and Spanish. Olivia also works in the field of computational linguistics as a data annotator and language data specialist.
This summer, I interned at SoundHound Inc. They develop voice-recognition, natural language understanding, and sound-recognition works with partners such as Honda, Pandora, Motorola, and Mercedes-Benz, integrating voice and conversation intelligence into products and services. As a language data specialist on the Spanish and English teams, I validated, curated, transcribed, and QAed speech training data. Though I’ve worked in data annotation and have ample experience in data management, this was a new application for my linguistic knowledge and an exciting challenge.
In machine learning, no detail is too small to overlook. Something as simple as the diacritic mark on the Spanish word cómo completely changes the word’s meaning, and although humans can rely on contextual cues and world knowledge to understand a phrase, machines don’t have that luxury. Every bit of data has to be accounted for, and in addition to the linguistic challenge of handling that volume of data, it also takes a great deal of coordination to make a team and project run smoothly. I was based in the new Boulder office, while the rest of the Spanish team was at headquarters in Santa Clara. Even at a tech company, somethings things go wrong with the Wifi, and all of us had to be adaptable and self-sufficient to get the work done.
After working a full day at SoundHound, I would return home to work on my second qualifying paper for my PhD program. As an academic, I’m a sociocultural linguist and conversation analyst. Essentially, I study how humans interact through conversation, and how people create, uphold, and challenge societal norms in everyday talk.
These two worlds may seem a bit disparate, and indeed in many traditional academic circles, exploring careers beyond the tenure-track is often called ‘alternative academic’ or even ‘non academic’. I’d like to challenge this binary a bit. As a language data specialist, all of my work has been highly academic. It takes very specialized linguistic knowledge and training to understand how to work with language data and how to approach challenges in artificial intelligence.
On the flip side, academic roles are often much more involved with the “real world” than many people assume. From our funding sources to our students, work inside universities is by no means separate from the cities and societies we live in, even if individual research topics can often appear removed from industry applications.
Linguists especially occupy a niche position between academia and industry. As the field of AI and voice recognition continues to grow, and as we encounter new challenges in product, policy, and performance, we need linguists leading paths towards the future. As linguists, we understand the technical aspects of language as well as how language functions as a broader system, and industry needs both of these perspectives. SoundHound clearly understands this need and has demonstrated the value they place in their interns. As a linguist, I’m glad I was one of them.
Thank you Olivia for sharing your experience with the Career Linguist community on our guest blog!
You can reach Olivia at email@example.com
Understanding Why Linguistics is Misunderstood
This guest blog was written by Patrick Goodridge who is a linguist, language teacher, and writer based in Philadelphia, PA. He will earn his BA in Linguistics from the University of Pennsylvania this May, and hopes to enter an MA program in Russian, East European, and Eurasian Studies thereafter. He also works as a linguistic adviser for 3ears.com, a new Russian language learning site.
Linguistics is the scientific study of language, though many who have heard of linguistics usually underestimate just how scientific it is. Those many are also sometimes unsure of what it is.
This is despite the advent of linguistic-based technology like Dragon (speech recognition), Google Translate (online machine translation), and now “smart speaker” devices like Amazon Echo. Even though the general populace uses these products regularly and with sincere fascination, the interest consumers have in these advances doesn’t extend to the field that originated them. For instance, when I tell people that I study linguistics, they usually say something like “That’s interesting, but…what exactly is linguistics, anyway?” I get the question often enough that I’ve even begun to couple my response with a definition: “I study linguistics, the science of language!” Skeptics will greet my answer with “Sooo what do you want to do with that?”, a question that can be uncomfortable and will seem painfully familiar to students in the humanities.
For young linguists, myself included, this lack of widespread understanding can be initially confusing and frustrating. In the past, I would even become somewhat offended by what I perceived as ignorance toward a field meaningful to me. When questioned about my interests or motives regarding linguistics, I’d launch straight into some pompous speech expounding the diversity in job offers, everywhere from Washington to Silicon Valley, that I’ve received because of my understanding of language and communication. The disconnect between fact and myth about the role of linguistics in the world seemed irreconcilable. How could (nearly) every human on this planet use language and yet be so oblivious to its study?
Truthfully, however, such a radical response was really a defense. It was a defense against feeling misunderstood, against feeling undervalued by society, and against the inevitable responsibility of defining for myself what linguistics means to me. But it is our task as scholars and professionals, not the task of everyone else, to define what it is the field means to us, and how we believe its principles can be best applied to the world.
Though this task is different for all of us, whether we work in educational, theoretical, or historical linguistics, we can nonetheless support one another. Some of us see our gifts as relevant to national defense, intercultural harmony, or diplomacy. Others see their gifts as relevant to technology, industry, and education, or to the crossroads of the three. For others, the goal is simply an understanding of language for the sake of knowledge itself. Those in this group seek to provide linguistic insight to others, whether that be deep insight provided to a graduate advisee under their tutelage, or broader insight to an undergraduate business major taking LING 101 to fulfill a science credit.
Such roles are meaningful to many in academia, and stimulating linguistic coursework in universities large and small will continue to be a vital part of informing the world about our field. Not all of us can teach, however, and so it will be essential for the rest of us to blaze our own trails in whatever area of technology, business, media, or government we feel language can most strongly impact.
I no longer resent others for not understanding linguistics or even for outright criticizing it as a choice of study. Instead, I realize that what makes the field valuable is not how well others understand it, but how well they understand what it can do for them. As a result, our goal should ultimately not be to make linguistics itself understood, but rather to make understood what exactly it is capable of. It can transform technology like it has in Google Translate’s new machine learning system. It can make learning the world’s most popular languages not only easier, but more enjoyable. It can even help us better understand our minds and, as a result, ourselves. The potentials are endless, as are your opportunities to make them a reality, and perhaps also to make linguistics better understood in the process.
You can reach Patrick at firstname.lastname@example.org or find links to his other work on LinkedIn.
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